Name: Spatial Data Visualization and Machine Learning in Python Course
Price: 25 GBP
Availability: InStock

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Get ready for an exceptional online learning experience with <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau</strong>bundle! This carefully curated collection of 20 premium courses is designed to cater to a variety of interests and disciplines. Dive into a sea of knowledge and skills, tailoring your learning journey to suit your unique aspirations.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">This Data Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau is a dynamic package that blends the expertise of industry professionals with the flexibility of digital learning. It offers the perfect balance of foundational understanding and advanced insights. Whether you&#39;re looking to break into a new field or deepen your existing knowledge, the<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"> Data Analysis </strong>package has something for everyone.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">As part of the Data Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau package, you will receive complimentary PDF certificates for all courses in <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analysis</strong> bundle at no extra cost. Equip yourself with the Data Analysis bundle to confidently navigate your career path or personal development journey. Enrol our <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analysis bundle today</strong> and start your career growth!</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">This </strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analysis </strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Bundle Comprises the Following CPD Accredited Courses:</strong></p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 1: </strong>Data Analytics</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 2: </strong>Diploma in Data Analytics with Tableau</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 3: </strong>Google Data Studio: Data Analytics</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 4: </strong>Business Intelligence Analyst</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 5: </strong>Diploma in Business Analysis</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 6: </strong>Data Science &amp; Machine Learning with Python</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 7: </strong>Spatial Data Visualization and Machine Learning in Python</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 8: </strong>Python Programming: Beginner To Expert</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 9: </strong>SQL For Data Analytics &amp; Database Development</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 10: </strong>Easy to Advanced Data Structures</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 11: </strong>R Programming for Data Science</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 12: </strong>Data Center Training Essentials: General Introduction</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 13: </strong>Data Analysis In Excel</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 14: </strong>Data Protection</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 15: </strong>Microsoft Excel Complete Course </li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 16: </strong>Career Development Plan Fundamentals</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 17: </strong>CV Writing and Job Searching</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 18: </strong>Learn to Level Up Your Leadership</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 19: </strong>Networking Skills for Personal Success</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 20: </strong>Ace Your Presentations: Public Speaking Masterclass</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Learning Outcome:</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">By completing the Data Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau course, you will:</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Gain comprehensive insights into multiple fields.</li><li fr-original-style="" style="box-sizing: border-box;">Foster critical thinking and problem-solving skills across various disciplines.</li><li fr-original-style="" style="box-sizing: border-box;">Understand industry trends and best practices through the<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"> Data Analysis</strong> Bundle.</li><li fr-original-style="" style="box-sizing: border-box;">Develop practical skills applicable to real-world situations.</li><li fr-original-style="" style="box-sizing: border-box;">Enhance personal and professional growth with the<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"> Data Analysis </strong>Bundle<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">.</strong></li><li fr-original-style="" style="box-sizing: border-box;">Build a strong knowledge base in your chosen course via the <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analysis </strong>Bundle.</li><li fr-original-style="" style="box-sizing: border-box;">Benefit from the flexibility and convenience of online learning.</li><li fr-original-style="" style="box-sizing: border-box;">With the <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analysis</strong> package, validate your learning with a CPD certificate.</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Each course in Data Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau bundle holds a prestigious CPD accreditation, symbolising exceptional quality. The materials, brimming with knowledge, are regularly updated, ensuring their relevance. This bundle promises not just education but an evolving learning experience. Engage with this extraordinary collection, and prepare to enrich your personal and professional development.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Embrace the future of learning with the Data Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau, a rich anthology of 15 diverse courses. Each course in the <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analysis</strong> bundle is handpicked by our experts to ensure a wide spectrum of learning opportunities. ThisData Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau bundle will take you on a unique and enriching educational journey.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">The bundle encapsulates our mission to provide quality, accessible education for all. Whether you are just starting your career, looking to switch industries, or hoping to enhance your professional skill set, the Data Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau bundle offers you the flexibility and convenience to learn at your own pace. Make the Data Analysis package your trusted companion in your lifelong learning journey.</p><h2 fr-original-style="" style="box-sizing: border-box;">
        
        <div fr-original-style="" style="box-sizing: border-box;">CPD</div>
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                                        200 CPD hours / points
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                                            Accredited by CPD Quality Standards
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        <div fr-original-style="" style="box-sizing: border-box;">Who is this course for?</div>
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                        <div id="who_is_this_course_for" fr-original-style="" style="box-sizing: border-box;">
                            <p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">The <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau</strong> bundle is perfect for:</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Enthusiasts:</strong> Keen to master data analysis tools like Python, Tableau, and Excel.</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Aspiring Business Analysts:</strong> Eager to derive actionable insights using data analysis techniques.</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">IT Professionals: </strong>Broadening skills with data analysis, machine learning, and business intelligence.</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Career Changers: </strong>Seeking a solid foundation in data analysis for a professional pivot.</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Leadership Aspirants: </strong>Complementing data analysis expertise with leadership and presentation skills.</li></ul>
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        <div fr-original-style="" style="box-sizing: border-box;">Requirements</div>
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                            <p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Without any formal requirements, you can delightfully enrol in this <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau</strong> course.</p>
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        <div fr-original-style="" style="box-sizing: border-box;">Career path</div>
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                            <p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Our bundle will prepare you for a range of careers, including:</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Data Analyst</li><li fr-original-style="" style="box-sizing: border-box;">Business Intelligence Analyst</li><li fr-original-style="" style="box-sizing: border-box;">Data Scientist</li><li fr-original-style="" style="box-sizing: border-box;">Python Developer</li><li fr-original-style="" style="box-sizing: border-box;">SQL Database Developer</li><li fr-original-style="" style="box-sizing: border-box;">Business Analyst</li><li fr-original-style="" style="box-sizing: border-box;">Data Protection Officer</li></ul>
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        <div fr-original-style="" style="box-sizing: border-box;">Certificates</div>
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                                    <h4 fr-original-style="" style="box-sizing: border-box;">Certificate Of Completion</h4>
        <p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">
            Digital certificate -
            Included
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        <h4 fr-original-style="" style="box-sizing: border-box;">Certificate Of Completion</h4>
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            Hard copy certificate -
            Included
        </p>
            <div fr-original-style="" style="box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">You will get a complimentary Hard Copy Certificate.</p></div>

                        </div>

NextGen Learning

Business Analytics & Intelligence

Big Data Analytics

Data Science

Data Skills

Data Analyst

Business Data Analysis

Data Analysis, Business Intelligence, Business Analysis with Python & Tableau - 20 Courses Bundle

General Admission

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			<h2>Overview
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					<p>Mastering data science skills and expertise can open new doors of opportunities for you in a wide range of fields. Learn the fundamentals and develop a solid grasp of Python data science with the comprehensive Data Science with Python course. This course is designed to assist you in securing a valuable skill set and boosting your career.</p><p>This course will provide you with quality training on the fundamentals of data analysis with Python. From the step-by-step learning process, you will learn the techniques of setting up the system. Then the course will teach you Python data structure and functions. You will receive detailed lessons on NumPy, Matplotlib, and Pandas. Furthermore, you will develop the skills for Algorithm Evaluation Techniques, visualising datasets and much more.</p><p>After completing the course you will receive a certificate of achievement. This certificate will help you create an impressive resume. So join today!</p>					</div>
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			<h2>How will I get my certificate?</h2>		</div>
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					<p><span>You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate.</span></p>					</div>
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			<h2>Who is This course for?</h2>		</div>
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					<p>This course Data Science with Python course is ideal for beginners in data science. It will help them develop a solid grasp of Python and help them pursue their dream career in the field of data science.</p>					</div>
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			<h2>Requirements</h2>		</div>
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					<p>The students will not require any formal qualifications or previous experience to enrol in this course. Anyone can learn from the course anytime from anywhere through smart devices like laptops, tabs, PC, and smartphones with stable internet connections. They can complete the course according to their preferable pace so, there is no need to rush.</p>					</div>
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			<h2>Career Path</h2>		</div>
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					<p>This course will equip you with valuable knowledge and effective skills in this area. After completing the course, you will be able to explore career opportunities in the fields such as</p><ul><li>Data Analyst </li><li>Data Scientist </li><li>Data Manager </li><li>Business Analyst</li></ul><p>And much more!</p>					</div>
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					</div> <h3>Course Curriculum</h3><div><p>90 sections • 90 lectures • 10:19:00 total length</p></div><div><div><div><div><div><div><div><p>•Course Overview &amp; Table of Contents: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Introduction to Machine Learning - Part 2 - Classifications and Applications: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•System and Environment preparation - Part 1: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•System and Environment preparation - Part 2: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of python - Assignment 1: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of python - Assignment 2: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of python - Functions: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of python - Data Structures: 00:12:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of NumPy - NumPy Array: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of NumPy - NumPy Data: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of NumPy - NumPy Arithmetic: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of Matplotlib: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of Pandas - Part 1: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of Pandas - Part 2: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Understanding the CSV data file: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Load and Read CSV data file using Python Standard Library: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Load and Read CSV data file using NumPy: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Load and Read CSV data file using Pandas: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Dataset Summary - Peek, Dimensions and Data Types: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Dataset Summary - Class Distribution and Data Summary: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Dataset Summary - Explaining Correlation: 00:11:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Dataset Summary - Explaining Skewness - Gaussian and Normal Curve: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Dataset Visualization - Using Histograms: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Dataset Visualization - Using Density Plots: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Dataset Visualization - Box and Whisker Plots: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Multivariate Dataset Visualization - Correlation Plots: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Multivariate Dataset Visualization - Scatter Plots: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Data Preparation (Pre-Processing) - Introduction: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Data Preparation - Re-scaling Data - Part 1: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Data Preparation - Re-scaling Data - Part 2: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Data Preparation - Standardizing Data - Part 1: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Data Preparation - Standardizing Data - Part 2: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Data Preparation - Normalizing Data: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Data Preparation - Binarizing Data: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Feature Selection - Introduction: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Feature Selection - Uni-variate Part 1 - Chi-Squared Test: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Feature Selection - Uni-variate Part 2 - Chi-Squared Test: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Feature Selection - Recursive Feature Elimination: 00:11:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Feature Selection - Principal Component Analysis (PCA): 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Feature Selection - Feature Importance: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Refresher Session - The Mechanism of Re-sampling, Training and Testing: 00:12:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Techniques - Introduction: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Techniques - Train and Test Set: 00:11:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Techniques - K-Fold Cross Validation: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Techniques - Leave One Out Cross Validation: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Techniques - Repeated Random Test-Train Splits: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - Introduction: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - Classification Accuracy: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - Log Loss: 00:03:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - Area Under ROC Curve: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - Confusion Matrix: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - Classification Report: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - Mean Absolute Error: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - Mean Square Error: 00:03:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - R Squared: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Classification Algorithm Spot Check - Logistic Regression: 00:12:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Classification Algorithm Spot Check - Linear Discriminant Analysis: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Classification Algorithm Spot Check - K-Nearest Neighbors: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Classification Algorithm Spot Check - Naive Bayes: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Classification Algorithm Spot Check - CART: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Classification Algorithm Spot Check - Support Vector Machines: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Regression Algorithm Spot Check - Linear Regression: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Regression Algorithm Spot Check - Ridge Regression: 00:03:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Regression Algorithm Spot Check - Lasso Linear Regression: 00:03:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Regression Algorithm Spot Check - Elastic Net Regression: 00:02:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Regression Algorithm Spot Check - K-Nearest Neighbors: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Regression Algorithm Spot Check - CART: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Regression Algorithm Spot Check - Support Vector Machines (SVM): 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Compare Algorithms - Part 1 : Choosing the best Machine Learning Model: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Compare Algorithms - Part 2 : Choosing the best Machine Learning Model: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Pipelines : Data Preparation and Data Modelling: 00:11:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Pipelines : Feature Selection and Data Modelling: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Performance Improvement: Ensembles - Voting: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Performance Improvement: Ensembles - Bagging: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Performance Improvement: Ensembles - Boosting: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Performance Improvement: Parameter Tuning using Grid Search: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Performance Improvement: Parameter Tuning using Random Search: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Export, Save and Load Machine Learning Models : Pickle: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Export, Save and Load Machine Learning Models : Joblib: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Finalizing a Model - Introduction and Steps: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Finalizing a Classification Model - The Pima Indian Diabetes Dataset: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Quick Session: Imbalanced Data Set - Issue Overview and Steps: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Iris Dataset : Finalizing Multi-Class Dataset: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Finalizing a Regression Model - The Boston Housing Price Dataset: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Real-time Predictions: Using the Pima Indian Diabetes Classification Model: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset: 00:03:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Real-time Predictions: Using the Boston Housing Regression Model: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Resources - Data Science &amp; Machine Learning with Python: 00:00:00</p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Apex Learning

Computing Skills

Data Engineering

Data Science with Python

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			<h2>Overview
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					<p><span>This comprehensive course on <b>Intermediate Python Coding</b> will deepen your understanding on this topic.</span></p><p><span>After successful completion of this course you can acquire the required skills in this sector. This <b>Intermediate Python Coding</b> comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market.</span></p><p><span>So enrol in this course today to fast track your career ladder.</span></p>					</div>
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			<h2>How will I get my certificate?</h2>		</div>
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					<p><span>You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate.</span></p>					</div>
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			<h2>Who is This course for?</h2>		</div>
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					<p><span>There is no experience or previous qualifications required for enrolment on this <b>Intermediate Python Coding</b>. It is available to all students, of all academic backgrounds.</span></p>					</div>
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			<h2>Requirements</h2>		</div>
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					<p><span>Our <b>Intermediate Python Coding</b> is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G.</span></p><p><span>There is no time limit for completing this course, it can be studied in your own time at your own pace.</span></p>					</div>
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			<h2>Career Path</h2>		</div>
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					<p>Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to-</p><ul><li>Open doors of opportunities</li><li>Increase your adaptability</li><li>Keep you relevant</li><li>Boost confidence</li></ul><p>And much more!</p>					</div>
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					</div> <h3>Course Curriculum</h3><div><p>10 sections • 59 lectures • 05:21:00 total length</p></div><div><div><div><div><div><div><div><p>•Course Introduction: 00:02:00</p></div><div><div><p>•Course Curriculum: 00:05:00</p></div><div><div><p>•How to get Pre-requisites: 00:02:00</p></div><div><div><p>•Getting Started on Windows, Linux or Mac: 00:01:00</p></div><div><div><p>•How to ask Great Questions: 00:02:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Introduction to Class: 00:07:00</p></div><div><div><p>•Create a Class: 00:09:00</p></div><div><div><p>•Calling a Class Object: 00:08:00</p></div><div><div><p>•Class Parameters - Objects: 00:05:00</p></div><div><div><p>•Access Modifiers(theory): 00:10:00</p></div><div><div><p>•Summary: 00:02:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Introduction to methods: 00:06:00</p></div><div><div><p>•Create a method: 00:07:00</p></div><div><div><p>•Method with parameters: 00:12:00</p></div><div><div><p>•Method default parameter: 00:06:00</p></div><div><div><p>•Multiple parameters: 00:05:00</p></div><div><div><p>•Method return keyword: 00:04:00</p></div><div><div><p>•Method Overloading: 00:05:00</p></div><div><div><p>•Summary: 00:02:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Introduction to OOPs: 00:05:00</p></div><div><div><p>•Classes and Objects: 00:08:00</p></div><div><div><p>•Class Constructors: 00:07:00</p></div><div><div><p>•Assessment Test1: 00:01:00</p></div><div><div><p>•Solution for Assessment Test1: 00:03:00</p></div><div><div><p>•Summary: 00:01:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Introduction: 00:04:00</p></div><div><div><p>•Inheritance: 00:13:00</p></div><div><div><p>•Getter and Setter Methods: 00:12:00</p></div><div><div><p>•Polymorphism: 00:13:00</p></div><div><div><p>•Assessment Test2: 00:03:00</p></div><div><div><p>•Solution for Assessment Test2: 00:03:00</p></div><div><div><p>•Summary: 00:01:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Introduction: 00:03:00</p></div><div><div><p>•Access Modifiers (public, protected, private): 00:21:00</p></div><div><div><p>•Encapsulation: 00:07:00</p></div><div><div><p>•Abstraction: 00:07:00</p></div><div><div><p>•Summary: 00:02:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Introduction: 00:01:00</p></div><div><div><p>•Dice Game: 00:06:00</p></div><div><div><p>•Card and Deck Game Playing: 00:07:00</p></div><div><div><p>•Summary: 00:01:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Introduction: 00:01:00</p></div><div><div><p>•PIP command installations: 00:12:00</p></div><div><div><p>•Modules: 00:12:00</p></div><div><div><p>•Naming Module: 00:03:00</p></div><div><div><p>•Built-in Modules: 00:03:00</p></div><div><div><p>•Packages: 00:08:00</p></div><div><div><p>•List Packages: 00:03:00</p></div><div><div><p>•Summary: 00:02:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Introduction: 00:02:00</p></div><div><div><p>•Reading CSV files: 00:11:00</p></div><div><div><p>•Writing CSV files: 00:04:00</p></div><div><div><p>•Summary: 00:01:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Introduction: 00:01:00</p></div><div><div><p>•Errors - Types of Errors: 00:08:00</p></div><div><div><p>•Try - ExceptExceptions Handling: 00:07:00</p></div><div><div><p>•Creating User-Defined Message: 00:05:00</p></div><div><div><p>•Try-Except-FinallyBlocks: 00:07:00</p></div><div><div><p>•Summary: 00:02:00</p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Online Course Creation

Computer Programming

Computer Skills

Professional Skills Course (PSC)

Trainers Course

Intermediate Python Coding

Studyhub UK

Programming Fundamentals

Python Basic Programming for Absolute Beginners

<p>Dive into the fascinating world of Python programming with our 'Python for Beginners Part 1' course. Python is a universal language with growing popularity and wide-ranging applications. This course is an excellent opportunity to unlock the power of Python, whether for personal or proficient growth. Start your journey with Python's fundamental concepts, advancing to data types and operators, and finally, mastering control flow mechanisms. This course lays the groundwork for more advanced topics, preparing you to become proficient in Python. By exploring Python for Beginners Part 1, you embark on a journey to acquiring one of the most sought-after skills in today's job market. Create your success story with Python and stay ahead in your skilled journey. Your step towards mastering Python starts here.</p><p><strong>Learning Outcomes:</strong></p><ul><li>Learn the basics of Python programming</li><li>Understand the different data types and operators in Python</li><li>Learn how to use data structures in Python</li><li>Learn how to control the flow of your code in Python</li></ul><p>This course begins with an introduction to Python, providing an overview of the language's fundamentals, guiding learners to set up Python on their local machines, and familiarising them with its syntax. The next module delves into Python's data types and operators, providing students with the knowledge to manipulate numbers, strings, and Booleans. Finally, in module four, we expand on these foundations by teaching the use of Python's core data structures: lists, dictionaries, sets, and tuples.</p><p>Module five delves into the control flow mechanisms in Python, covering topics such as conditional statements, loops, and exception handling. These mechanisms are vital for creating programs to make decisions, repeat tasks, and handle errors. Throughout the course, the learners are encouraged to apply the learned principles and techniques to real-world problems, thus developing a practical understanding of Python.</p><p><strong>Certification</strong></p><p>Upon successful completion of the course, all learners will be eligible to receive a certificate titled Python For Beginners Part 1 to acknowledge their achievement. We are delighted to offer two formats for your certificate: PDF and Hardcopy.</p><ul><li><strong>PDF Certificate:</strong> This digital version of your certificate will be available for you to download and print for totally <strong>FREE</strong>. </li><li><strong>Hardcopy Certificate (UK Delivery):</strong> For those who wish to have a physical token of their achievement, we offer a high-quality, printed certificate. This hardcopy certificate is also provided free of charge. However, please note that delivery fees apply. If your shipping address is within the United Kingdom, the delivery fee will be only <strong>£3.99</strong>.</li><li><strong>Hardcopy Certificate (International Delivery): </strong>For all international addresses outside of the United Kingdom, the delivery fee for a hardcopy certificate will be only <strong>£10</strong>. </li></ul><h2>
        
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                                        10 CPD hours / points
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                                            Accredited by CPD Quality Standards
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                            <p>This course is for anyone looking to start their journey into programming, explicitly using Python. It's perfect for beginners with little or no prior knowledge of Python or any other programming language. Individuals interested in data analysis, web development, artificial intelligence, or learning a new skill might find this course beneficial. Students, teachers, hobbyists, or entrepreneurs seeking to automate tasks or make sense of data can leverage Python's simplicity and versatility.</p>
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                            <ul><li>Data Analyst - £25K to £40K/year.</li><li>Software Developer - £30K to £55K/year.</li><li>Web Developer - £24K to £50K/year.</li><li>Automation Engineer - £35K to £60K/year.</li><li>Machine Learning Engineer - £40K to £70K/year.</li></ul>
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                                    <h4>Digital certificate</h4>
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            Digital certificate -
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        <h4>Hard copy certificate</h4>
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            Hard copy certificate -
            Included
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            <div><p><strong>Hardcopy Certificate (UK Delivery):</strong></p><p>For those who wish to have a physical token of their achievement, we offer a high-quality, printed certificate. This hardcopy certificate is also provided free of charge. However, please note that delivery fees apply. If your shipping address is within the United Kingdom, the delivery fee will be only <strong>£3.99</strong>.</p><p><strong>Hardcopy Certificate (International Delivery): </strong></p><p>For all international addresses outside of the United Kingdom, the delivery fee for a hardcopy certificate will be only <strong>£10</strong>.</p></div>

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Training Express

Get Up and Running with Python Course

<p>The world of Artificial Intelligence (AI) is rapidly expanding, with new breakthroughs and applications emerging every day. If you're looking to stay ahead of the curve, then look no further than our comprehensive course, "Learn AI with Python." Through a combination of engaging modules and real-world case studies, our course covers everything from the basics of AI to advanced techniques for detecting patterns and natural language processing.</p><p>With a particular focus on Python programming language, learners will gain insights into Class Imbalance and Grid Search, Adaboost Regressor, Affinity Propagation Model, Gaussian Mixture Model, Logic Programming, Heuristic Search and more. Whether you're a beginner or an experienced programmer, our course will take you on a journey through the fascinating and ever-changing world of AI.</p><p>By the end of the course, learners will be equipped with the knowledge and skills to create AI models and programs that can solve real-world problems. With our expert guidance and in-depth analysis, you'll gain the knowledge and confidence to make informed decisions and navigate the complex and dynamic world of AI. Don't miss out on this opportunity to enhance your skills and advance your career - enroll in "Learn AI with Python" today and join the ranks of successful AI programmers around the world.</p><p><strong>Learning Outcomes:</strong></p><ul><li>Develop an understanding of the principles and practices of Artificial Intelligence (AI)</li><li>Learn effective strategies for detecting patterns and natural language processing</li><li>Develop analytical skills for creating AI models and programs</li><li>Understand Python programming language and its applications in AI</li><li>Be able to make informed decisions and navigate the complex and dynamic world of AI</li></ul><p>The "Learn AI with Python" course is designed to provide a comprehensive understanding of the principles and practices that underpin successful AI programming. Through engaging modules and real-world case studies, learners will gain insights into the basics of AI, advanced techniques for detecting patterns and natural language processing, and effective strategies for creating AI models and programs using Python programming language.</p><p>By the end of the course, learners will be equipped with the knowledge and skills to make informed decisions and navigate the complex and dynamic world of AI. Whether you're a beginner or an experienced programmer, this course is a must-have for anyone interested in the world of AI.</p><p><strong>â±â± Learn AI with Python</strong><strong> Course Curriculum </strong></p><ul><li><strong>Section 01: </strong>Introduction<strong><br /></strong></li><li><strong>Section 02: </strong>Class Imbalance and Grid Search<strong><br /></strong></li><li><strong>Section 03: </strong>Adaboost Regressor<strong><br /></strong></li><li><strong>Section 04: </strong>Detecting patterns with Unsupervised Learning<strong><br /></strong></li><li><strong>Section 05: </strong>Affinity Propagation Model<strong><br /></strong></li><li><strong>Section 06: </strong>Clustering Quality<strong><br /></strong></li><li><strong>Section 07: </strong>Gaussian Mixture Model<strong><br /></strong></li><li><strong>Section 08: </strong>Classifiers<strong><br /></strong></li><li><strong>Section 09: </strong>Logic Programming<strong><br /></strong></li><li><strong>Section 10: </strong>Heuristic Search<strong><br /></strong></li><li><strong>Section 11: </strong>Natural Language Processing</li></ul><p><strong>How is the course assessed?</strong></p><p>Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%.</p><p><strong>Exam &amp; Retakes:</strong><br />It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable.</p><p><strong>Certification</strong><br />Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery).</p><h2>
        
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                                        10 CPD hours / points
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                                            Accredited by CPD Quality Standards
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        <div>Who is this course for?</div>
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                            <ul><li>Programmers looking to enhance their AI skills</li><li>Business professionals interested in AI applications</li><li>Computer science students interested in AI</li><li>Entrepreneurs looking to incorporate AI into their products or services</li><li>Anyone interested in gaining a comprehensive understanding of AI and its applications</li></ul>
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                            <p>There are no formal entry requirements for the course, with enrollment open to anyone!</p>
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                            <ul><li>AI Programmer: £30,000 - £70,000 per year</li><li>Data Scientist: £30,000 - £80,000 per year</li><li>Machine Learning Engineer: £35,000 - £90,000 per year</li><li>AI Researcher: £40,000 - £100,000 per year</li><li>Software Developer: £25,000 - £70,000 per year</li></ul>
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                                    <h4>Certificate of completion</h4>
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            Digital certificate -
            £9
        </p>
            <div> <p>You can apply for a CPD Accredited PDF Certificate at the cost of £9.</p> </div>
        <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            £15
        </p>
            <div> <p>Hard copy can be sent to you via post at the expense of £15.</p> </div>

                        </div>

One Education

Learn AI with Python Course

Computer Science With Python Course

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				<p><span>Register on the Python for Spatial Analysis in ArcGIS today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career.</span></p><p><span>The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials.</span></p><p><span>Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get an e-certificate as proof of your course completion.</span></p><p><span>The Python for Spatial Analysis in ArcGIS is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones.</span></p><p><span>The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly!</span></p><h5><b>What You Get With The Python for Spatial Analysis in ArcGIS </b></h5><ul><li><span>Receive a e-certificate upon successful completion of the course</span></li><li><span>Get taught by experienced, professional instructors</span></li><li><span>Study at a time and pace that suits your learning style</span></li><li><span>Get instant feedback on assessments </span></li><li><span>24/7 help and advice via email or live chat</span></li><li><span>Get full tutor support on weekdays (Monday to Friday)</span></li></ul>					</div>
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			<h2>Course Design</h2>		</div>
				</div>
				<div>
				<div>
								<div>
				<div id="course-home"><div><p><span>The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace.</span></p><p><span>You are taught through a combination of</span></p><ul><li><span>Video lessons</span></li><li><span>Online study materials</span></li></ul></div></div>					</div>
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			<h2>Certification</h2>		</div>
				</div>
				<div>
				<div>
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				<p><span>Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99.</span></p>					</div>
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			<h2>Who Is This Course For:</h2>		</div>
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				<p><span>The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge.</span></p>					</div>
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			<h2>Requirements:</h2>		</div>
				</div>
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				<p><span>The online training is open to all students and has no formal entry requirements. To study the Python for Spatial Analysis in ArcGIS, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16.</span></p>					</div>
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					</div><div>
				<h3>Course Content</h3>

<div id="course_curriculum">
<table width="100%">				<tbody><tr>
					<td colspan="4">Python for Spatial Analysis in ArcGIS</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Introduction of batch processing</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 02: Link a series of processes to one</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 03: Animation of feature data 1</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 04: Animation of feature data 2</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 05: Animation of raster data 1</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 06: Animation of raster data 2</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 07: Collect data and Batch processing</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 08: Hydrological processing with python script</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Module 09: Map Algebra and Math 1</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Module 10: Map Algebra and Math 2</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 11: Display XY, Select and Export</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 12: Surface and Interpolation</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Assignment</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Assignment - Python for Spatial Analysis in ArcGIS</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
				</tbody></table></div>

			</div>
			<h2>Frequently Asked Questions</h2>
                        <div>
                            <div>
                                <span>
                                    Are there any prerequisites for taking the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        There are no specific prerequisites for this course, nor
                                        are there any formal entry requirements. All you need is
                                        an internet connection, a good understanding of English
                                        and a passion for learning for this course.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    Can I access the course at any time, or is there a set
                                    schedule?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        You have the flexibility to access the course at any time
                                        that suits your schedule. Our courses are self-paced,
                                        allowing you to study at your own pace and convenience.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    How long will I have access to the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        For this course, you will have access to the course
                                        materials for 1 year only. This means you can review the
                                        content as often as you like within the year, even after
                                        you've completed the course. However, if you buy Lifetime
                                        Access for the course, you will be able to access the
                                        course for a lifetime.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    Is there a certificate of completion provided after
                                    completing the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        Yes, upon successfully completing the course, you will
                                        receive a certificate of completion. This certificate can
                                        be a valuable addition to your professional portfolio and
                                        can be shared on your various social networks.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    Can I switch courses or get a refund if I'm not satisfied
                                    with the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        We want you to have a positive learning experience. If
                                        you're not satisfied with the course, you can request a
                                        course transfer or refund within 14 days of the initial
                                        purchase.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    How do I track my progress in the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        Our platform provides tracking tools and progress
                                        indicators for each course. You can monitor your progress,
                                        completed lessons, and assessments through your learner
                                        dashboard for the course.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    What if I have technical issues or difficulties with the
                                    course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        If you encounter technical issues or content-related
                                        difficulties with the course, our support team is
                                        available to assist you. You can reach out to them for
                                        prompt resolution.
                                    </p>
                                </div>
                            </div>
                        </div>

Janets

Python for Spatial Analysis in ArcGIS

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				<div>
			<h4>Overview</h4>		</div>
				</div>
				</div>
		<div>
				<div>
				<div>
							<p><span>By enroling in Spatial Data Visualization and Machine Learning in Python, you can kickstart your vibrant career and strengthen your profound knowledge. You can learn everything you need to know about the topic.</span></p><p><span>The Spatial Data Visualization and Machine Learning in Python course includes all of the most recent information to keep you abreast of the employment market and prepare you for your future. The curriculum for this excellent Spatial Data Visualization and Machine Learning in Python course includes modules at all skill levels, from beginner to expert. You will have the productivity necessary to succeed in your organisation once you have completed our Spatial Data Visualization and Machine Learning in Python Program.</span></p><p><span>So enrol in our Spatial Data Visualization and Machine Learning in Python course right away if you're keen to envision yourself in a rewarding career.</span></p>						</div>
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			<h4>Description</h4>		</div>
				</div>
				</div>
		<div>
				<div>
				<div>
							<p><span>Enroling in this Spatial Data Visualization and Machine Learning in Python course can improve your Spatial Data Visualization and Machine Learning in Python perspective, regardless of your skill levels in the Spatial Data Visualization and Machine Learning in Python topics you want to master. If you're already a Spatial Data Visualization and Machine Learning in Python expert, this peek under the hood will provide you with suggestions for accelerating your learning, including advanced Spatial Data Visualization and Machine Learning in Python insights that will help you make the most of your time. This Spatial Data Visualization and Machine Learning in Python course will act as a guide for you if you've ever wished to excel at Spatial Data Visualization and Machine Learning in Python.</span></p>						</div>
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				<div>
			<h4>Why Choose Us?</h4>		</div>
				</div>
				</div>
		<div>
				<div>
				<div>
					<ul>
							<li>
											<span>
													</span>
										<span>This course is accredited by the CPD Quality Standards.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Lifetime access to the whole collection of the learning materials.</span>
									</li>
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											<span>
													</span>
										<span>Online test with immediate results.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Enroling in the course has no additional cost.</span>
									</li>
								<li>
											<span>
													</span>
										<span>You can study and complete the course at your own pace.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Study for the course using any internet-connected device, such as a computer, tablet, or mobile device.</span>
									</li>
						</ul>
				</div>
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		<div>
				<div>
				<div>
			<h4>Will I Receive A Certificate Of Completion?</h4>		</div>
				</div>
				</div>
		<div>
				<div>
				<div>
							<p>Upon successful completion, you will qualify for the UK and internationally-recognised CPD certificate and you can choose to make your achievement formal by obtaining your PDF Certificate at a cost of £4.99 and Hardcopy Certificate for £9.99.</p>						</div>
				</div>
				</div>
					</div>
				</div>
		<div>
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		<div>
				<div>
				<div>
			<h4>Who Is This Course For?</h4>		</div>
				</div>
				</div>
		<div>
				<div>
				<div>
							<p><span>This Spatial Data Visualization and Machine Learning in Python course is a great place to start if you're looking to start a new career in Spatial Data Visualization and Machine Learning in Python field. This training is for anyone interested in gaining in-demand Spatial Data Visualization and Machine Learning in Python proficiency to help launch a career or their business aptitude. </span></p>						</div>
				</div>
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				</div>
		<div>
				<div>
				<div>
			<h4>Requirements</h4>		</div>
				</div>
				</div>
		<div>
				<div>
				<div>
							<p><span>The Spatial Data Visualization and Machine Learning in Python course requires no prior degree or experience. All you require is English proficiency, numeracy literacy and a gadget with stable internet connection. Learn and train for a prosperous career in the thriving and fast-growing industry of Spatial Data Visualization and Machine Learning in Python, without any fuss.</span></p>						</div>
				</div>
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				<div>
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			<h4>Career Path</h4>		</div>
				</div>
				</div>
		<div>
				<div>
				<div>
							<p><span>This Spatial Data Visualization and Machine Learning in Python training will assist you develop your Spatial Data Visualization and Machine Learning in Python ability, establish a personal brand, and present a portfolio of relevant talents. It will help you articulate a  Spatial Data Visualization and Machine Learning in Python professional story and personalise your path to a new career. Furthermore, developing this Spatial Data Visualization and Machine Learning in Python skillset can lead to numerous opportunities for high-paying jobs in a variety of fields.</span></p>						</div>
				</div>
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				<div>
			<h4>Order Your Certificate</h4>		</div>
				</div>
				</div>
		<div>
				<div>
				<div>
							<div><div><div><div id="1693981461.590199"><div><div><div><div><div><div><div><div><div><div><div>To order CPD Quality Standard Certificate, we kindly invite you to visit the following link:</div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>						</div>
				</div>
				<div>
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						<span>
						
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		</div>
				</div>
				</div>
				</div>
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				</div> <div>
				<h3>
	<span>Course Curriculum</span>
</h3>

<div>
<table>				<tbody><tr>
					<td colspan="4">Section 01: Introduction</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction</td>
					<td> </td>
					<td><span><i></i> 00:14:00</span></td>
				</tr>
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					<td colspan="4">Section 02: Setup and Installations</td>
				</tr>
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					<td><i></i></td>
					<td>Python Installation</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Installing Bokeh</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 03: Data Preparation</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Preparation</td>
					<td> </td>
					<td><span><i></i> 00:24:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 04: Data Visualization</td>
				</tr>
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					<td><i></i></td>
					<td>Creating a Bar Chart</td>
					<td> </td>
					<td><span><i></i> 00:18:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating a Line Chart</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating a Doughnut Chart</td>
					<td> </td>
					<td><span><i></i> 00:22:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating a Magnitude Plot</td>
					<td> </td>
					<td><span><i></i> 00:31:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating a Geo Map Plot</td>
					<td> </td>
					<td><span><i></i> 00:20:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating a Grid Plot</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 05: Machine Learning</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Pre-processing</td>
					<td> </td>
					<td><span><i></i> 00:21:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Building a Predictive Model</td>
					<td> </td>
					<td><span><i></i> 00:21:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Building a Prediction Dataset</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 06: Building the Dashboard</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Adding predicted data to our plots - Part 1</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Adding predicted data to our plots - Part 2</td>
					<td> </td>
					<td><span><i></i> 00:14:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Adding predicted data to our plots - Part 3</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Adding the Grid Plot</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 07: Creating the Dashboard Server</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Installing Visual Studio Code</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating the Project and Virtual Environment</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Building and Running the Server</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 08: Project Source Code</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Resources</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Order Your Certificate</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Order Your Certificate</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
				</tbody></table></div>

			</div>

Spatial Data Visualization and Machine Learning in Python Course

London

<article>
<div>
<h5>Java EVENINGS Course</h5>
</div>
<div></div>
<p>  						 
	</p><div>
	<ul>
		<p>
		<b>Python EVENINGS Course. </b>Basic Python syntax and principles of Object Orientated Programming. 
		<br />Most attendees are in-work IT Professional.
		<br />Private individuals are also very welcome. 
		<br />Evening courses also running.
		<br /><b>Our Style: </b>Hands-on, Practical  
		<br /><b>Location:  </b>Online, Instructor-led  
		<br /><b>Download:  </b>anaconda.com
		<br /><b>Duration:  </b>6 weeks, 1 evening per week, 6pm - 8pm
		<br /><b>Times: </b>arrange a time for your time zone
	    </p>
	</ul>	

<p></p>
</div></article>

<div>
	  <div>
		 <h5>Python Basics EVENINGS Course </h5>
	  </div>
	  <div></div>
	  <p> 
 
				This Python course London Evening covers the essential Python Basics, in our interactive, instructor led Live Virtual Classroom.
				This Python Basics course is a very good introduction to essential fundamental programming concepts using Python as programming language.
				These concepts are daily used by programmers and is your first step to working as a programmer.
				By the end, you'll be comfortable in programming Python code.
				You will have done small projects.
				This will serve for you as examples and samples that you can use to build larger projects.
				You can publish your code online to keep as a portfolio.

<br />
This Python Programming course is hands-on and practical, to give you in-depth, practical experience of the topics covered.

	  </p>
	<div>
	<h5>Week 1: Basics</h5>
	</div>
	<div></div>
	<div> 
					<p>  <strong>Python Data Types and Variables:</strong>  
					<br />  Primitive types; Characters &amp; Strings; Boolean; Working with variables and its scope; Conversion and casting types in Python.	 
					<br /> <strong>Operators and Expressions: </strong>   
					<br />  Introduction of operators; Arithmetic operators; Relational operators; Assignment operator; Logical operators; Increment and decrement operators.
					</p> 
			 
				<p><strong> Decision Making:</strong>
				<br />If statement; If - else statement; If- elif - else statement; Nested if - else.
				</p><p><strong>Using Loops:</strong>
				<br />The while, while-else.
				<br />For loop;
				<br />Jump statements: break, continue;
				<br />Nesting loops.				
				</p>
			</div>
	<div>
	<h5>Week 2: Data Structures</h5>
	</div> <div></div>
	<div> 
				<p> Lists.
					<br />Tuples.
					<br />Sets.
					<br />Dictionary. Nested Dictionary.
					<br />Json Files.
				</p>
			</div>
	<div>
	<h5>Week 3: Python built-in functions</h5>
	</div> <div></div>
	<div> 
				<p>  
				<br />Using Built-in modules and functions:
				<br />Strings Functions.
				<br />Pattern matching with Regex.
				<br />Maths Functions.
				<br />Random Functions.
				<br />Python Date functions.
				</p>
			</div>
	<div>
	<h5>Week 4: OOP: Using Modules, functions, classes</h5>
	</div> <div></div>
	<div>
				<p>  Creating and using custom Functions.
					<br />Creating functions;
					<br />Using parameters and return values;
					<br />
					<br />Introduction to Classes and Objects:
					<br />Creating a Class; 
					<br />Creating an Object; Using an Object; 
					<br />Adding Instance variables; Controlling accessibility; Naming conventions for class members. 
					<br /> Class Constructors; Parameterized Constructors.
					<br />Inheritance. Overload.
				</p>
			</div>

	<div>
	<h5>Week 5: Pandas DataBase Basics</h5>
	</div> <div></div>
	<div>	 
		<p> <b>Connection details:</b>
				Connect to a database using access codes. 
				<br /><b>Select Queries:</b>
				Retrieving records and iterating results sets, using variables and parameters in queries. 
				<br />Working with DDL comands:
				Create a database, drop a database.
				Create a table, alter tables, drop a table. 
				<br />Working with DML Commands:
				Insert, delete, update records.
		</p>
	</div>
	
	 
	<div>
	<h5>Week 6: Pandas Dataframe Basics</h5>
	</div> <div></div>
	<div>	 
		<p> Getting data into a dataframe:
			<br />Dict to Dataframe, Dataframe to Dict.
			<br />Excel To Dict, Dict to Excel , working with Excel data, multiple Excel sheets.

			<br />Dataframe basics:
			<br />Slicing Dataframes,
			<br />Getting information about the dataframe,
			<br />Filter, sort and query a Dataframes,
			<br />Duplicate values,
			<br />Working with null-values,
			<br />Sampling,
			<br />Group by,
			<br />Join.

		</p>
	</div>
	  
</div>
 

<div>   

	   <div id="cincluded">
		  <div>
			 <h5>What is included</h5>
		  </div>

		  <article>
		  <div>
			 <ul>
				<li>PCWorkshops Course Certificate on completion  </li>
									   
				<li>Python Course Notes</li>
				<li>Python Code Examples</li>
				<li>Practical Python Course exercises and Code Samples</li>
				<li>After the course: 1-Hour personalised online revision session</li>
			 </ul>
		  </div>
		  </article>
	   </div>
				    
<div>
	                  <div>
	                     <h5 id="cincluded2">Book the Python  Course</h5>
	                  </div>
 
<div id="eventbrite-widget-container-60636103217"></div>




							 
</div>
				   <div id="caboutus">
	                  <div>
	                     <h5>About us</h5>
	                  </div> 
	                  	<article>
					    <div>
					    	<div>
					    		<div>
					    			
					    			<h5>Our experienced trainers are award winners. </h5> 
					    			<ul>
										<li>
											More about us
										</li>
										<li>
											FAQ's
										</li>
										<li>
											Client Comments  
										</li>
									 </ul>
					    		</div>
					    		<div>
					    			
					    				
					    			
					    		</div>
					    	</div>
	                     
					    </div>
					    </article>						
	               </div>
				   
				   
	        </div>

Python EVENINGS Course
Basic Python syntax and principles of object-oriented programming. 
Most attendees are in-work IT Professional. 
Private individuals are also very welcome. 
Evening courses also running. 

Details:
Our Style: Hands-on, Practical 
Location: Online, Instructor-led 
Download: anaconda.com 
Duration: 4 weeks, 1 evening per week, 6pm - 8pm 
Times: arrange a time for your time zone 
How to attend:  
Connection Link For the course: https://meet.goto.com/910697125
Once you have made the payment, use the above link on the date booked, to connect with the trainer. 
Python Basics EVENINGS Course
 This Python course London Evening covers the essential Python Basics, in our interactive, instructor led Live Virtual Classroom. This Python Basics course is a very good introduction to essential fundamental programming concepts using Python as programming language. These concepts are daily used by programmers and is your first step to working as a programmer. By the end, you'll be comfortable in programming Python code. You will have done small projects. This will serve for you as examples and samples that you can use to build larger projects. You can publish your code online to keep as a portfolio. 

This Python Programming course is hands-on and practical, to give you in-depth, practical experience of the topics covered. 
Week 1: Basics
 Python Data Types and Variables: 
Primitive Data types; Working with variables and its scope; Conversion and casting types in Python. 
 Operators and Expressions:  
 Introduction of operators; Arithmetic operators; Relational operators; Assignment operator; Logical operators; Increment and decrement operators. 
 Decision Making: 
If statement; If - else statement; If- elif - else statement; Nested if - else. 
Using Loops: 
The while, while-else. 
For loop; 
Jump statements: break, continue; 
Nesting loops. 
Week 2: Data Structures & Database
Lists.  
Tuples. 
Sets. 
Dictionary. Nested Dictionary. 
Json Files. 
Reading csv and text files
Connecting with a database and run SQL Queries. 
Week 3: Python built-in functions &  Pandas Dataframe Basics
 
Using built-in modules and functions: 
Strings Functions. 
Maths Functions. 
Random Functions. 
Data Frames; 
Getting data into a dataframe: 
Dict to Dataframe, Dataframe to Dict.  
Dataframe basics: 
Slicing Dataframes, 
Getting information about the dataframe, 
Filter and query a Dataframes, 
Working with null-values.
Week 4: OOP: Using Modules, functions, classes
 Creating and using custom Functions. 
Creating functions; 
Using parameters and return values; 
 
Introduction to Classes and Objects: 
Creating a Class; 
Creating an Object; Using an Object; 
Adding instance variables; controlling accessibility; and naming conventions for class members. 
 Class Constructors; Parameterized Constructors. 
Inheritance. Overload. 

What is included
PCWorkshops Course Certificate on completion
Python Course Notes
Python Code Examples
Practical Python Course exercises and Code Samples
After the course: 1-Hour personalised online revision session
  

PCWorkshops

Instructor

Python

Basic Python syntax and principles of Object Orientated Programming. 
Most attendees are in-work IT Professional. 
Private individuals are also very welcome. 
Evening courses also running. 
Our Style: Hands-on, Practical 
Location: Online, Instructor-led 
Download: anaconda.com 
Duration: 6 weeks, 1 evening per week, 6pm - 8pm 
Times: arrange a time for your time zone 

Python EVENINGS Course, Online Instructor-led

General admission

<div style="color: rgb(57, 54, 79); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(57, 54, 79);"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">This Python BootCamp is Instructor-led, Practical. In the12-week Python course, learn start to in-depth, leading to a good Python career.</strong></p></div><div data-testid="organizerBrief" fr-original-style="" style="box-sizing: border-box;"><div data-testid="creator-signal-main-section" fr-original-style="" style="box-sizing: border-box;"><section fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></section></div></div></div><div data-testid="organizerBrief" fr-original-style="" style="box-sizing: border-box;"><div data-testid="creator-signal-main-section" fr-original-style="" style="box-sizing: border-box;"><section fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></section></div></div></div><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><div style="color: rgb(57, 54, 79); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(57, 54, 79);"><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">PYTHON BOOTCAMP:</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">This 12-week Python Boot Camp is a practical, instructor-lead program, covering Python from start to in-depth. You will be fully fluent and confident as a Python programmer.</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">If you have more questions goto&nbsp;<a href="http://pcworkshopslondon.co.uk/contact.html" target="_blank" rel="nofollow noopener noreferrer" data-airgap-id="66" style="color: var(--eds-control,#3659e3); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: var(--eds-control,#3659e3);">https://pcworkshopslondon.co.uk/contact.html&nbsp;</a>,</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Or&nbsp;<a href="https://pcworkshopslondon.co.uk/" target="_blank" rel="nofollow noopener noreferrer" data-airgap-id="67" style="color: var(--eds-control,#3659e3); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: var(--eds-control,#3659e3);">contact us on training@pcworkshopslondon.co.uk</a></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><a href="https://pcworkshopslondon.co.uk/contact.htm" target="_blank" rel="nofollow noopener noreferrer" data-airgap-id="68" style="color: var(--eds-control,#3659e3); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: var(--eds-control,#3659e3);">C﻿ustomise dates, course outline, arrange installments</a></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">This course will give you enough&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">practical experience and practical projects</strong>&nbsp;to code, to give you full confidence to enter into the coding profession. &nbsp;&nbsp;</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Duration:&nbsp;</strong>3 months:</p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">1 Python class per week,</li><li fr-original-style="" style="box-sizing: border-box;">Plus pratical work,</li><li fr-original-style="" style="box-sizing: border-box;">Plus personal trainer-mentor for 1-1 training,</li><li fr-original-style="" style="box-sizing: border-box;">Plus e-learning materials.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Final project :&nbsp;</strong>Practical to upload to&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">GitHub&nbsp;</strong>and show-case</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Date and times, choose:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Fridays in London or Online&nbsp;</strong>, 10am - 5pm,</li><li fr-original-style="" style="box-sizing: border-box;">or&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Saturdays in London or Online&nbsp;</strong>, 12noon-6pm,</li><li fr-original-style="" style="box-sizing: border-box;">o﻿r negotiate your date</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Study level:</strong> Start from beginners level to in-depth, ready to work professionally.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Virtual attendance: &nbsp;</strong>online instructor-led&nbsp;</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Download</strong>: Anaconda.com</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Pre-requisites:&nbsp;</strong>General computer literacy.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Oracle Qualification:&nbsp;</strong>PCWorkshops Python Programmer Certificate</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Payments:</strong>&nbsp; You may apply to pay in installments for this Python Training course</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">COURSE OUTLINE</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">W﻿eek 1 - 4: Essentials</strong></p><ol fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Python Coding Basics</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Object Oriented programming:&nbsp;</strong>Python Object Orientated programming (OOP)</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">UX Principles:&nbsp;</strong>UX Principles and applying it on Front-ends with TKinter</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Specialised topics:&nbsp;</strong>Dates, Localization, Strings, Maths Operation , Random Number,&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Lambdas</strong></li></ol><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">W﻿eek 5 - 10 : All about data</strong></p><ol fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Data Structures:</strong>&nbsp;Lists, Tuples, Sets,&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Exceptions</strong>, I/O Fundamentals , Reading and Writing file</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Database:&nbsp;</strong>Database principles and SQL.&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Database Project:&nbsp;</strong>Python database connections and creating a database driven project</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analytics:&nbsp;</strong>Numpy. Pandas for data analytics and data queries.</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analytics:&nbsp;</strong>Pandas data cleaning and restructuring, interacticting with Excel, Csv, Json,etc.</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data visualisation:&nbsp;</strong>MatPlotLib</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Prediction:&nbsp;</strong>Machine Learning Basics</li></ol><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">W﻿eek 11 and 12: The final touch</strong></p><ol fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Concurrency and Multi-threading:</strong>&nbsp;Threads vs. Processes, Threading Module, Threading Event, Stop a Thread, Daemon Threads, Thread-safe Queue, Thread Pools, Locks</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Unit Testing</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">O﻿ptional&nbsp;</strong>: Replace Week 11 or 12 with Scraping using Python, ot Tkinter Front-ends</li></ol><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">I﻿NCLUDED:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">PCWorkshops Python Course Certificate on completion.</li><li fr-original-style="" style="box-sizing: border-box;">Python Course notes.</li><li fr-original-style="" style="box-sizing: border-box;">Practical Course exercises, Code Examples, Online Materials.</li><li fr-original-style="" style="box-sizing: border-box;">After the course, continuous assistance with practical and preparation for exams</li><li fr-original-style="" style="box-sizing: border-box;">Max group size on this is 4.</li><li fr-original-style="" style="box-sizing: border-box;">Portfolio: Post your Python project online.</li><li fr-original-style="" style="box-sizing: border-box;">Exam preparation and interview questions</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">MORE ABOUT THE ONLINE CLASSROOM</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">&nbsp;Attend from your internet connection</li><li fr-original-style="" style="box-sizing: border-box;">&nbsp;Instructor-led, get instant answers to your questions</li><li fr-original-style="" style="box-sizing: border-box;">&nbsp;Fully interactive</li><li fr-original-style="" style="box-sizing: border-box;">&nbsp;Work clearly explained with demonstrations and examples</li><li fr-original-style="" style="box-sizing: border-box;">&nbsp;Practical exercises to be tried out by delegate</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">WHAT YOU WILL GAIN:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Skills &amp; knowledge: Python coding knowledge and understanding with good practical application &nbsp;</li><li fr-original-style="" style="box-sizing: border-box;">Certification:&nbsp;Internal PCWorkshops Python certificate</li><li fr-original-style="" style="box-sizing: border-box;">Portfolio: You will have an online portfolio of Python projects&nbsp;</li><li fr-original-style="" style="box-sizing: border-box;">Experience:&nbsp;Our comprehensive practical makes you job ready</li></ul></div><div data-testid="image-content" style="color: rgb(57, 54, 79); box-sizing: border-box;" fr-original-style=" color: rgb(57, 54, 79);"><img src="https://img.evbuc.com/https%3A%2F%2Fcdn.evbuc.com%2Fimages%2F444528299%2F44980801875%2F1%2Foriginal.20230212-111230?h=2000&w=720&auto=format%2Ccompress&q=75&sharp=10&s=bc03bf9766e6c9ca0436ac60d0be83d6" alt="" data-airgap-id="88" fr-original-style="" style="cursor: pointer; padding: 0px 1px; user-select: none; max-width: 100%; position: relative; box-sizing: border-box;" fr-original-class="fr-draggable"></div><div data-testid="image-content" style="color: rgb(57, 54, 79); box-sizing: border-box;" fr-original-style=" color: rgb(57, 54, 79);"><img src="https://img.evbuc.com/https%3A%2F%2Fcdn.evbuc.com%2Fimages%2F588336959%2F44980801875%2F1%2Foriginal.20230901-170557?h=2000&w=720&auto=format%2Ccompress&q=75&sharp=10&s=e4036ff76e1af36cfba9452461b16c48" alt="" data-airgap-id="87" fr-original-style="" style="cursor: pointer; padding: 0px 1px; user-select: none; max-width: 100%; position: relative; box-sizing: border-box;" fr-original-class="fr-draggable"></div><div data-testid="image-content" style="color: rgb(57, 54, 79); box-sizing: border-box;" fr-original-style=" color: rgb(57, 54, 79);"><img src="https://img.evbuc.com/https%3A%2F%2Fcdn.evbuc.com%2Fimages%2F588337149%2F44980801875%2F1%2Foriginal.20230901-170614?h=2000&w=720&auto=format%2Ccompress&q=75&sharp=10&s=cdf1fcea5ad47abc354df67b458d5237" alt="" data-airgap-id="89" fr-original-style="" style="cursor: pointer; padding: 0px 1px; user-select: none; max-width: 100%; position: relative; box-sizing: border-box;" fr-original-class="fr-draggable"></div><div data-testid="image-content" style="color: rgb(57, 54, 79); box-sizing: border-box;" fr-original-style=" color: rgb(57, 54, 79);"><img src="https://img.evbuc.com/https%3A%2F%2Fcdn.evbuc.com%2Fimages%2F588337349%2F44980801875%2F1%2Foriginal.20230901-170630?h=2000&w=720&auto=format%2Ccompress&q=75&sharp=10&s=839d02fa3087d55ac858bcbb697972f5" alt="" data-airgap-id="86" fr-original-style="" style="cursor: pointer; padding: 0px 1px; user-select: none; max-width: 100%; position: relative; box-sizing: border-box;" fr-original-class="fr-draggable"></div></div><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></p><div style="color: rgb(30, 10, 60); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(30, 10, 60);"><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><h2 fr-original-style="" style="box-sizing: border-box;">Refund Policy</h2></div><div style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">No Refunds</div>

This Python Data Analytics BootCamp is Instructor-led, Practical. In the12-week Python course, learn start to in-depth, leading to a good Python career.



PYTHON BOOTCAMP:
This 12-week Python Data Analytics Data Boot Camp is designed to give you a complete skill set required by data analysts .
You will be fully fluent and confident as a Python  data analyst, with full understanding of Python Programming.
From Data, databases, datasets, importing, cleaning, transforming, analysing to visualisation and creating awesome dashboards
The course is a practical, instructor-lead program.

If you have more questions goto https://pcworkshopslondon.co.uk/contact.html,
Or contact us on training@pcworkshopslondon.co.uk
C﻿ustomise dates, course outline, arrange installments
This course will give you enough practical experience and practical projects to code, to give you full confidence to enter into the coding profession. 
Duration: 3 months, 12 weeks:
1 Python class per week,
Plus practical work,
Plus personal trainer-mentor for 1-1 training,
Plus e-learning materials.
Final project : Practical to upload to GitHub and show-case
Date and times, choose:
Fridays in London or Online , 10am - 5pm,
or Saturdays in London or Online , 12noon-6pm,
o﻿r negotiate your date
Study level: Start from beginners level to in-depth, ready to work professionally.
Virtual attendance: online instructor-led 
Download: Anaconda.com
Pre-requisites: General computer literacy.
Oracle Qualification: PCWorkshops Python Programmer Certificate
Payments: You may apply to pay in installments for this Python Training course
COURSE OUTLINE
W﻿eek 1 - 4: Essentials
Python Coding Basics
Object Oriented programming: Python Object Orientated programming (OOP)
UX Principles: UX Principles and applying it on Front-ends with TKinter
Specialised topics: Dates, Localization, Strings, Maths Operation , Random Number, Lambdas
W﻿eek 5 - 10 : All about data
Python Data Structures: Lists, Tuples, Sets, Exceptions, I/O Fundamentals , Reading and Writing file
Database: Database principles and SQL. Database Project: Python database connections and creating a database driven project
Data Analytics: Numpy. Pandas for data analytics and data queries.
Data Analytics: Pandas data cleaning and restructuring, interacticting with Excel, Csv, Json,etc.
Data visualisation: MatPlotLib
Prediction: Machine Learning Basics
W﻿eek 11 and 12: The final touch
Python Concurrency and Multi-threading: Threads vs. Processes, Threading Module, Threading Event, Stop a Thread, Daemon Threads, Thread-safe Queue, Thread Pools, Locks
Python Unit Testing
O﻿ptional : Replace Week 11 or 12 with Scraping using Python, ot Tkinter Front-ends
I﻿NCLUDED:
PCWorkshops Python Course Certificate on completion.
Python Course notes.
Practical Course exercises, Code Examples, Online Materials.
After the course, continuous assistance with practical and preparation for exams
Max group size on this is 4.
Portfolio: Post your Python project online.
Exam preparation and interview questions
MORE ABOUT THE ONLINE CLASSROOM
Attend from your internet connection
Instructor-led, get instant answers to your questions
Fully interactive
Work clearly explained with demonstrations and examples
Practical exercises to be tried out by delegate
WHAT YOU WILL GAIN:
Skills & knowledge: Python coding knowledge and understanding with good practical application
Certification: Internal PCWorkshops Python certificate
Portfolio: You will have an online portfolio of Python projects
Experience: Our comprehensive practical makes you job ready






Refund Policy
No Refunds

PYTHON BOOTCAMP:



This 12-week Python Data Analytics Data Boot Camp is designed to give you a complete skill set required by data analysts .



You will be fully fluent and confident as a Python  data analyst, with full understanding of Python Programming.



From Data, databases, datasets, importing, cleaning, transforming, analysing to visualisation and creating awesome dashboards



The course is a practical, instructor-lead program.



Python Data Analytics BootCamp, 12-weeks, Online Instructor-led

Python Bootcamp Saturdays, Online

<article>
					<div>
						<h5>Python Beginners Course, 1-Day.</h5>
					</div>
					<div></div>
					<p>
						<span> </span>
						<br />This course covers the essential Python Basics, in our interactive, instructor led Live Virtual Classroom.
						<br />	This Python Basics course is a very good introduction to essential fundamental programming concepts using Python as programming language.
							<br />These concepts are daily used by programmers and is your first step to working as a programmer.
							<br />By the end, you'll be comfortable in programming Python code.
							<br />You will have done small projects.
							<br />This will serve for you as examples and samples that you can use to build larger projects.
						 
						<br /><b>Location: </b>Instructor-led, Online.
						<br /><b>Our Style: </b>Hands-on, Practical Course.
						<br /><b>Group Size: </b>Max 4 people per group.  
						<br /><b>Qualification: </b>PCWorkshops Beginners Certification
						<br /><b>Hours: </b>1 Day, 10am-5pm
						<br /><b>Download: </b>anaconda.com
						
				  	</p>
	    		</article> 
				
				<article>
					<div>
						<h5>Python Beginners Course, Course Outline.</h5>
					</div>
					<div></div>
					<p>
						<span> </span>
						<br />
						<b>Session 1: Basics</b>
 
						<br />Python Data Types and Variables:
						Working with variables and its scope; Conversion and casting types in Python.
						<br />Operators and Expressions.
						 

						<br />Decision Making: If statement; If - else statement; If- elif - else statement; Nested if - else. 
						
						<br />Using Loops: The while, while-else. For loop; Jump statements: break, continue; Nesting loops.
<br />
						<br /><b>Session 2: Data Structures</b>
						 
						<br />Lists.
						<br />Tuples.
						<br />Sets.
						<br />Dictionary. Nested Dictionary.
						<br />Json Files.
<br />
						<br /><b>Session 3: Python Built-in functions</b> 
						<br />Strings Functions. 
						<br />Maths Functions.
						<br />Random Functions.
						<br />Python Date functions.
<br />
						<br /><b>Session 4: OOP: Using Modules, functions, classes</b>
						 
						<br />Creating and using custom Functions.
						
						<br />Using parameters and return values.

						<br />Introduction to Classes and Objects:
						<br />Creating a Class. Creating and using Objects. 
						<br />Class Constructors.
						<br />Inheritance. Overload.
<br />
						<br /><b>Session 5: Access SQL Database Via Python</b>
						 
						<br /><b>Connection details:</b> Connect to a database using access codes.
						<br /><b>Select Queries:</b> Retrieving records and iterating results sets, using variables and parameters in queries.
						<br /><b>Working with DDL comands: </b>Create a database, drop a database. Create a table, alter tables, drop a table.
						<br /><b>Working with DML Commands: </b>Insert, delete, update records.

						<br /><br /><br /><b>Session 6: Pandas Dataframe Basics</b>
						 
						<br />Getting data into a dataframe:
						<br />Dict to Dataframe, Dataframe to Dict.
						<br />Excel To Dict, Dict to Excel , working with Excel data, multiple Excel sheets.
						<br />Dataframe basics:
						<br />Slicing Dataframes, Querying, filter and sort a dataframe,
						
						<br />Working with duplicates and null-values, Sampling, Group by, Join.
						
						
						
				  	</p>
	    		</article> 

			    <div>  
				     
	     
	               <div id="cincluded">
	                  <div>
	                     <h5>Python Beginners Course Materials</h5>
	                  </div>

	                  <article>
	                  <div>
	                     <ul>
	                        <li>Python Beginners Certificate on completion  </li>
							                  
						    <li>Python Beginners Notes</li>
							<li>Python Code Examples</li>
	                        <li>Practical Python Beginners exercises</li>
	                        
	                     </ul>
	                  </div>
						   
	                  </article>
	               </div>
			
				    <article>
					<div>
						<h5>More about Python</h5>
					</div>
					<div></div>
					<p>
							Python is the Easiest Programming Language to Learn 
				 				Anybody can learn how to use it and  entry-level coders get access to the industry in a 
									fast-tacked manner and can from there migrate to other languages.
								 <br />
								 Learning to code  is now more important than ever, since a growing number of application and <br />
								  digital products require programmers. <br />

								 Additionally, as an interpreted coding language, Python allows you to run each line of code <br />
								 after writing it, rather 
								 than other compiled languages, such as C++. <br />
								 This is particularly useful for beginners, as they can test their work and 
								  gain instant feedback, <br />
								  to make amendments where required and continuously improve. A Python Course will
								explain to you how to do this<br />
								  <br />
								 Python is a Versatile Coding Language <br />
								 Use it for : <br /> 
								 Data mining ,  Data analytics , Data visualisation ,  AI and machine learning,  Building apps ,
								 Web development and web application development ,  Developing games,  Quantitative and qualitative analysis,
								 Data Engineering,  A Python Course is the start of all of the above.
								 <br /><br />
								 Learning Python will Improve Your Job Prospects <br />
								 As the fastest-growing computer programming language in the world, 
								 Python is also one of the most in-demand jobs. According to 2022 LinkedIn data,   
								Python is the second most in-demand programming language, after Java.  
								All of this makes a Python Course essential. 
				  	</p>
	    		</article> 
					  
				    
					
					
					
				   <div id="booking">
	                  <div>
	                     <h5>Book the Python Beginners Course</h5>
	                  </div>
							 
 							<div id="eventbrite-widget-container-48024956939"></div>

							

							
							 
	               </div>
				   <div id="cincluded">
	                  <div>
	                     <h5>About us</h5>
	                  </div> 
	                  	<article>
					    <div>
					    	<div>
					    		<div>
					    			
					    			<h5>Our experienced trainers are award winners. </h5> 
					    			<ul>
										<li>
											More about us
										</li>
										<li>
											FAQ's
										</li>
										<li>
											Client Comments  
										</li>
									 </ul>
					    		</div>
					    		<div>
					    			
					    				
					    			
					    		</div>
					    	</div>
	                     
					    </div>
					    </article>						
	               </div>
				   
				   
	            </div>

Python Beginners Course, 1-Day.
   
This course covers the essential Python Basics, in our interactive, instructor led Live Virtual Classroom. 
	This Python Basics course is a very good introduction to essential fundamental programming concepts using Python as programming language. 
These concepts are daily used by programmers and is your first step to working as a programmer. 
By the end, you'll be comfortable in programming Python code. 
You will have done small projects. 
This will serve for you as examples and samples that you can use to build larger projects. 

Location: Instructor-led, Online. 
Our Style: Hands-on, Practical Course. 
Group Size: Max 4 people per group. 
Qualification: PCWorkshops Beginners Certification 
Hours: 1 Day, 10am-5pm 
Download: anaconda.com 
Python Beginners Course, Course Outline.
  Session 1: Basics 
Python Data Types and Variables: Working with variables and its scope; Conversion and casting types in Python. 
Operators and Expressions. 
Decision Making: If statement; If - else statement; If- elif - else statement; Nested if - else. 
Using Loops: The while, while-else. For loop; Jump statements: break, continue; Nesting loops.

 
Session 2: Data Structures 
Lists. 
Tuples. 
Sets. 
Dictionary. Nested Dictionary. 
Json Files.

 
Session 3: Python Built-in functions 
Strings Functions. 
Maths Functions. 
Random Functions. 
Python Date functions.

 
Session 4: OOP: Using Modules, functions, classes 
Creating and using custom Functions. 
Using parameters and return values. 
Introduction to Classes and Objects: 
Creating a Class. Creating and using Objects. 
Class Constructors. 
Inheritance. Overload.

 
Session 5: Access SQL Database Via Python 
Connection details: Connect to a database using access codes. 
Select Queries: Retrieving records and iterating results sets, using variables and parameters in queries. 
Working with DDL comands: Create a database, drop a database. Create a table, alter tables, drop a table. 
Working with DML Commands: Insert, delete, update records. 


Session 6: Pandas Dataframe Basics 
Getting data into a dataframe: 
Dict to Dataframe, Dataframe to Dict. 
Excel To Dict, Dict to Excel , working with Excel data, multiple Excel sheets. 
Dataframe basics: 
Slicing Dataframes, Querying, filter and sort a dataframe, 
Working with duplicates and null-values, Sampling, Group by, Join. 
Python Beginners Course Materials
Python Beginners Certificate on completion
Python Beginners Notes
Python Code Examples
Practical Python Beginners exercises
More about Python
 Python is the Easiest Programming Language to Learn Anybody can learn how to use it and entry-level coders get access to the industry in a fast-tacked manner and can from there migrate to other languages. 
 Learning to code is now more important than ever, since a growing number of application and 
 digital products require programmers. 
 Additionally, as an interpreted coding language, Python allows you to run each line of code 
 after writing it, rather than other compiled languages, such as C++. 
 This is particularly useful for beginners, as they can test their work and gain instant feedback, 
 to make amendments where required and continuously improve. A Python Course will explain to you how to do this
 
 Python is a Versatile Coding Language 
 Use it for : 
 Data mining , Data analytics , Data visualisation , AI and machine learning, Building apps , Web development and web application development , Developing games, Quantitative and qualitative analysis, Data Engineering, A Python Course is the start of all of the above. 

 Learning Python will Improve Your Job Prospects 
 As the fastest-growing computer programming language in the world, Python is also one of the most in-demand jobs. According to 2022 LinkedIn data, Python is the second most in-demand programming language, after Java. All of this makes a Python Course essential. 
 

Programming Languages

his course covers the essential Python Basics, in our interactive, instructor led Live Virtual Classroom. 
	This Python Basics course is a very good introduction to essential fundamental programming concepts using Python as programming language. 
These concepts are daily used by programmers and is your first step to working as a programmer. 
By the end, you'll be comfortable in programming Python code. 
You will have done small projects. 
This will serve for you as examples and samples that you can use to build larger projects. 

Python Beginners Course, 1-Day

<article>
<div>
<h5>Python Data Analytics Course</h5>
</div>
<div></div>
<p>  						 
	</p><div>
	<ul>
		
<div>
    <div id="widget-reviews"><div><h3>Python Beginners Course</h3><div><span></span><span></span><span></span><span></span><span></span><div>(4.6)</div></div><span></span><br /><div>Based on 5 reviews</div><div><div><div id="previous"><i></i></div><div id="currentReview"><div> Excellent course, led by a knowledg</div><div> Excellent course, led by a knowledgeable and engaging instructor. I attended ...</div><div> Helen S</div></div><div id="next"><i></i></div></div></div></div></div>
    <div id="widget-link">
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</div>

		<p>
		<b>Python Data Course. </b>Data Analytics with Python using Numpy, Pandas, Dataframes. 
		<br />Most attendees are in-work Data Professional.
		<br />Private individuals are very welcome. 
		<br /><b>Our Style: </b>Hands-on, Practical  
		<br /><b>Location:  </b>Online, Instructor-led  
		<br /><b>Download:  </b>anaconda.com
		<br /><b>Duration:  </b>2 consecutive days, 10am - 5pm
		<br /><b>Times: </b>arrange a time for your time zone
	    </p>
	</ul>	

<p></p>
</div></article>

<div>
	  <div>
			<h5>Python Data Analytics Course </h5>
	  </div>
	  <div></div>
	  <p>  
	  <br /> 
	  </p>
	<div>
	<h5>Session 1: Database: </h5>
	</div>
	<div></div>
	<div> 
					<p>  <strong>SQLite3:</strong>  
					<br /> Linking with SQL Database.
					<br /> Create, Amend and Drop Tables.
					<br /> Insert, Update and delete records.
					<br /> Select queries.
					<br /> Traverse and display query results.
					<br /> Using parameters in queries.
					<br /> Get metadata about tables and columns. 
					</p> 
			</div>
	<div>
	<h5>Session 2: Data Structures</h5>
	</div> <div></div>
	<div> 
				<p> <strong>Data Structures:</strong>  
					<br />Tuples.
					<br />Sets.
					<br />Dictionary. Nested Dictionary.
					<br />Json Files.
				</p>
			</div>
	<div>
	<h5>Session 3: Python Numpy</h5>
	</div> <div></div>
	<div> 
				<p>  <strong>Numpy:</strong>  
				<br />The Python NumPy Module:
				<br />Working with arrays, create data using arrays.
				<br />Array manipulation.
				<br />String functions on arrays. 
				<br />Math, arithmetic and statistical functions.
				
				</p>
			</div>
	<div>
	<h5>Session 4: Python Pandas Dataframes and data importing</h5>
	</div> <div></div>
	<div>
		<p>  <strong>Python Dataframes</strong>  
		<br /> Data Series. Date/ Time Functionality. Time series.
		<br /> Creating Dataframes, Indexing. 
		<br />Dict to Dataframe, Dataframe to Dict.
		<br />Csv to Dataframe, Dataframe to csv.
		<br />Excel to Dataframe, Dataframe to Excel.
		</p>
	</div>

	<div>
	<h5>Session 5: Data Cleaning and preparation</h5>
	</div> <div></div>
	<div>	 
		<p> <strong>Data Cleaning and preparation</strong>  
		<br />Finding, replacing and filtering missing data.
		<br />Remove Duplicates.
		<br />Replacing values.
		<br />Renaming Axis Indexes.
		</p>
	</div>
	
	<div>
	<h5>Session 6: Pandas Data Wrangling</h5>
	</div> <div></div>
	<div>	 
		<p> <strong>Data Wrangling:</strong>   
		
		<br />Indexing, Re-indexing, 
		<br />Reorder, 
		<br />Sorting, Stastitics, 
			<br />Transforming data using  
		<br />Dataframe Joins, Merging, Concatenation, Overlap, Append, zip. 
		 
		</p>
	</div>
	
	<div>
	<h5>Week 6: Pandas Data Analysis</h5>
	</div> <div></div>
	<div>	 
		<p> <strong>Data Analysis:</strong>   
		<br /> Sorting. 
		<br /> Analysing and finding data using filter, slicing and dataframe queries. 
		<br /> Finding data by Iteration.
		<br /> Find statistics: Functions, Aggregate functions. 
		<br /> Unique values.
		<br />String objects, Regex. 
		</p>
	</div>
</div>
 

<div>   

	   <div id="cincluded">
		  <div>
			 <h5>Included with the Python Course</h5>
		  </div>

		  <article>
		  <div>
			 <ul>
				<li>PCWorkshops Course Certificate on completion  </li>
									   
				<li>Python Course Notes</li>
				<li>Python Code Examples</li>
				<li>Practical Python Course exercises and Code Samples</li>
				<li>After the course: 1-Hour personalised online revision session</li>
			 </ul>
		  </div>
		  </article>
	   </div>
				    
<div>
	                  <div>
	                     <h5 id="cincluded2">Book the Python Course</h5>
	                  </div>
 
	 
		<div id="eventbrite-widget-container-48025096356"></div>
		
		  		
					
					 
</div>
				   <div id="caboutus">
	                  <div>
	                     <h5>About us</h5>
	                  </div> 
	                  	<article>
					    <div>
					    	<div>
					    		<div>
					    			
					    			<h5>Our experienced trainers are award winners. </h5> 
					    			<ul>
										<li>
											More about us
										</li>
										<li>
											FAQ's
										</li>
										<li>
											Client Comments  
										</li>
									 </ul>
					    		</div>
					    		<div>
					    			
					    				
					    			
					    		</div>
					    	</div>
	                     
					    </div>
					    </article>						
	               </div>
				   
				   
	        </div>

Python Data Analytics Course

Python Data Analytics with Python using 
Numpy, 
Pandas, Dataframes. 

Most attendees are in-work Data Professional.  Private individuals are very welcome. 
Our Style: Hands-on, Practical 
Location: Online, Instructor-led 
Download: anaconda.com 
Duration: 1 consecutive day, 11am-5pm
Dates Times: You may let us know which dates your would prefer, or attend as scheduled

Python Data Analytics Course Description
  
Session 1: Database:
 SQLite3: 
 Linking with SQL Database. 
 Create, Amend and Drop Tables. 
 Insert, Update and delete records. 
 Select queries. 
 Traverse and display query results. 
 Using parameters in queries. 
 Get metadata about tables and columns. 
Session 2: Data Structures
 Data Structures: 
Tuples. 
Sets. 
Dictionary. Nested Dictionary. 
Json Files. 
Session 3: Python Numpy
 Numpy: 
The Python NumPy Module: 
Working with arrays, create data using arrays. 
Array manipulation. 
String functions on arrays. 
Math, arithmetic and statistical functions. 
Session 4: Python Pandas Dataframes and data importing
 Python Dataframes 
 Data Series. Date/ Time Functionality. Time series. 
 Creating Dataframes, Indexing. 
Dict to Dataframe, Dataframe to Dict. 
Csv to Dataframe, Dataframe to csv. 
Excel to Dataframe, Dataframe to Excel. 
Session 5: Data Cleaning and preparation
 Data Cleaning and preparation 
Finding, replacing and filtering missing data. 
Remove Duplicates. 
Replacing values. 
Renaming Axis Indexes. 
Session 6: Pandas Data Wrangling
 Data Wrangling: 
Indexing, Re-indexing, 
Reorder, 
Sorting, Stastitics, 
Transforming data using 
Dataframe Joins, Merging, Concatenation, Overlap, Append, zip. 
Week 6: Pandas Data Analysis
 Data Analysis: 
 Sorting. 
 Analysing and finding data using filter, slicing and dataframe queries. 
 Finding data by Iteration. 
 Find statistics: Functions, Aggregate functions. 
 Unique values. 
String objects, Regex. 
Included with the Python Course
PCWorkshops Course Certificate on completion
Python Course Notes
Python Code Examples
Practical Python Course exercises and Code Samples
After the course: 1-Hour personalised online revision session
 

Pandas

Python Data Analytics with Python using 



Numpy, 




Pandas, Dataframes. 





Most attendees are in-work Data Professional.  Private individuals are very welcome. 
Our Style: Hands-on, Practical 
Location: Online, Instructor-led 



Python Data Analytics Course

<article>
<div>
<h5>Java Machine Learning Course</h5>
</div>
<div></div>
<p>  						 
	</p><div>
	<ul>
		<p>
		<b>Python Machine Learning Course. </b>
		<br /><b>Prerequisites: </b>Basic knowledge of Python 
		<br /><b>Our Style: </b>Hands-on, Practical  
		<br /><b>Location:  </b>Online, Instructor-led  
		<br /><b>Download:  </b>anaconda.com
		<br /><b>Duration:  </b>2 consecutive days, the first of which shows as the booking date.
		<br /><b>Times: </b>10am - 5pm
	    </p>
	</ul>	

<p></p>
</div></article>

<div>
	  <div>
		 <h5>Python Machine Learning Course </h5>
	  </div>
	  <div></div>
		<p> Python Machine Learning algorithms can derive trends (learn) from data and make predictions on data by extrapolating on existing trends. Companies can take advantage of this to gain insights and ultimately improve business.
		<br />
		<br />Using Python Machine Learning scikit-learn, practice how to use Python Machine Learning algorithms to perform predictions on data.
		<br />
		<br />Learn the below listed algorithms, a small collection of available Python Machine Learning algorithms.
		<br />
		<br />Gain a good understanding of how to plan a Machine Learning project.
		We create, experiment and run example code to implement the Python Machine Learning algorithms.
	  </p>
<div>
<h5>Course Topics</h5>
</div>
<div></div>
<div>
	<ul>	  
			<li>Supervised Machine Learning:
			<strong>Classification Algorithms:</strong>  	 
					Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine
					<br /><strong>Regression Algorithms:</strong>  Linear, Polynomial
			</li> 
	
	
			<li> <strong>  Unsupervised Machine Learning: </strong> Clustering Algorithms: K-means clustering, Hierarchical Clustering

			<br /><strong>Dimension Reduction Algorithms: </strong>Principal Component Analysis Latent Dirichlet allocation (LDA)

			<br /><strong>Association Algorithms:</strong> Apriori, Euclat

			<br /><strong>Other machine learning Algorithms:</strong>
			Reinforcement learning Algorithms: Q-Learning
			</li>
	
			<li>
			<strong>Ensemble Methods Algorithms:</strong> Stacking, bagging, boosting.
			</li> 
			
			<li>
			<strong>Random </strong>Forest Random Forest, Gradient Boosting
			</li> 
	 
		<li><strong>Neural Networks and Deep Leaning Algorithms:</strong>
		Convolutional Network (CNN)
		</li> 
		
		<li><strong>Data Exploration and Preprocessing:</strong> The first part of a Machine Learning project understands the data and the problem at hand. Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy. 
		</li>
	
		<li> Injecting domain knowledge in the process, attributes are extracted from the data and engineered into Machine Learning algorithms.
		</li> 
</ul>
</div>
		  
		
		 
</div>

Python Scikit-Learn Machine Learning Course


Prerequisites: Basic knowledge of Python 
Our Style: Hands-on, Practical 
Location: Online, Instructor-led 
Download: anaconda.com 
Duration: 1 days
Times: 11am - 5pm 
How to attend: 
You can select your dates and use the link  https://meet.goto.com/910697125  to attend
Python Machine Learning Course Description
 Python Machine Learning algorithms can derive trends (learn) from data and make predictions on data by extrapolating on existing trends. Companies can take advantage of this to gain insights and ultimately improve business. 
 
Using Python Machine Learning scikit-learn, practice how to use Python Machine Learning algorithms to perform predictions on data. 
 
Learn the below listed algorithms, a small collection of available Python Machine Learning algorithms. 
 
Gain a good understanding of how to plan a Machine Learning project. We create, experiment, and run example code to implement the Python Machine Learning algorithms. 
Course Topics
Supervised Machine Learning: Classification Algorithms: Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine 
Regression Algorithms: Linear, Polynomial
Unsupervised Machine Learning: Clustering Algorithms: K-means clustering, Hierarchical Clustering 
Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA) 
Association Algorithms: Apriori, Euclat 
Other machine learning Algorithms: Reinforcement learning Algorithms: Q-Learning
Ensemble Methods Algorithms: Stacking, bagging, boosting.
Random Forest Random Forest, Gradient Boosting
Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN)
Data Exploration and Preprocessing: The first part of a Machine Learning project understands the data and the problem at hand. Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy.
Injecting domain knowledge in the process, attributes are extracted from the data and engineered into Machine Learning algorithms.

Unsupervised Machine Learning

Python Machine Learning algorithms can derive trends (learn) from data and make predictions on data by extrapolating on existing trends. Companies can take advantage of this to gain insights and ultimately improve business. 
 
Using Python Machine Learning scikit-learn, practice how to use Python Machine Learning algorithms to perform predictions on data. 
 
Learn the below listed algorithms, a small collection of available Python Machine Learning algorithms. 

Python Machine Learning, online instructor-led 

<div style="color: rgb(57, 54, 79); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(57, 54, 79);"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">This Python Machine Learning online instructor led course is an excellent introduction to popular machine learning algorithms.</strong></p></div><div data-testid="organizerBrief" fr-original-style="" style="box-sizing: border-box;"><div data-testid="creator-signal-main-section" fr-original-style="" style="box-sizing: border-box;"><section fr-original-style="" style="box-sizing: border-box;"></section></div></div><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></strong></p><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Machine Learning 2-day Course</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><em fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Prerequisites:</strong></em></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Basic knowledge of Python coding is a pre-requisite.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><em fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Who Should Attend?</strong></em></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">This course is an overview of machine learning and machine learning algorithms in Python SciKitLearn.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Practical:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">We cover the below listed algorithms, which is only a small collection of what is available. However, it will give you a good understanding, to plan your Machine Learning project</li><li fr-original-style="" style="box-sizing: border-box;">We create, experiment and run machine learning sample code to implement a short selected but representative list of available the algorithms.&nbsp;</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course Outline:</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Supervised Machine Learning:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine</li><li fr-original-style="" style="box-sizing: border-box;">Regression Algorithms: Linear, Polynomial</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Unsupervised Machine Learning:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Clustering Algorithms: K-means clustering, Hierarchical Clustering</li><li fr-original-style="" style="box-sizing: border-box;">Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA)</li><li fr-original-style="" style="box-sizing: border-box;">Association Machine Learning Algorithms: Apriori, Euclat</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Other machine learning Algorithms:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Ensemble Methods ( Stacking, bagging, boosting ) Algorithms: Random Forest, Gradient Boosting</li><li fr-original-style="" style="box-sizing: border-box;">Reinforcement learning Algorithms: Q-Learning</li><li fr-original-style="" style="box-sizing: border-box;">Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN)</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Exploration and Preprocessing:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">The first part of a Machine Learning project understands the data and the problem at hand.</li><li fr-original-style="" style="box-sizing: border-box;">Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">What is included in this Python Machine Learning:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Python Machine Learning Certificate on completion &nbsp;</li><li fr-original-style="" style="box-sizing: border-box;">Python Machine Learning notes</li><li fr-original-style="" style="box-sizing: border-box;">Practical Python Machine Learning exercises and code examples</li><li fr-original-style="" style="box-sizing: border-box;">After the course, 1 free, online session for questions or revision Python Machine Learning.</li><li fr-original-style="" style="box-sizing: border-box;">Max group size on this Python Machine Learning is 4.</li></ul></div><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></p><div style="color: rgb(30, 10, 60); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(30, 10, 60);"><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><h2 fr-original-style="" style="box-sizing: border-box;">Refund Policy</h2></div><div style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">No Refunds</div>

This Python Machine Learning online instructor led course is an excellent introduction to popular machine learning algorithms.





Python Machine Learning 2-day Course
Prerequisites:
Basic knowledge of Python coding is a pre-requisite.
Who Should Attend?
This course is an overview of machine learning and machine learning algorithms in Python SciKitLearn.
Practical:
We cover the below listed algorithms, which is only a small collection of what is available. However, it will give you a good understanding, to plan your Machine Learning project
We create, experiment and run machine learning sample code to implement a short selected but representative list of available the algorithms.
Course Outline:
Supervised Machine Learning:
Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine
Regression Algorithms: Linear, Polynomial
Unsupervised Machine Learning:
Clustering Algorithms: K-means clustering, Hierarchical Clustering
Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA)
Association Machine Learning Algorithms: Apriori, Euclat
Other machine learning Algorithms:
Ensemble Methods ( Stacking, bagging, boosting ) Algorithms: Random Forest, Gradient Boosting
Reinforcement learning Algorithms: Q-Learning
Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN)
Data Exploration and Preprocessing:
The first part of a Machine Learning project understands the data and the problem at hand.
Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy.


What is included in this Python Machine Learning:
Python Machine Learning Certificate on completion
Python Machine Learning notes
Practical Python Machine Learning exercises and code examples
After the course, 1 free, online session for questions or revision Python Machine Learning.
Max group size on this Python Machine Learning is 4.





Refund Policy
No Refunds

Python Machine Learning Course, 1-Days, Online Attendance

Python Basics 1-days Online Instructor-Led

<div style="color: rgb(57, 54, 79); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(57, 54, 79);"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python coding, interactive, instructor-led, hands-on, practical. From basics to working with professionals. Python Part Time. Python Coding.</strong></p></div><div data-testid="organizerBrief" fr-original-style="" style="box-sizing: border-box;"><div data-testid="creator-signal-main-section" fr-original-style="" style="box-sizing: border-box;"><section fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></section></div></div></div><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Beginners Evenings Course</strong></strong></p><h2 style="color: rgb(30, 10, 60); box-sizing: border-box;" fr-original-style=" color: rgb(30, 10, 60);">Course summary</h2><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">This Python Programming course has become essential to all professional who would like to do code using Python. Learn evenings, work while studying. Work and study Python Part Time.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">It is a Python beginners course and teaches Python coding from scratch to intermediate.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Hands-on, practical. We code some real life examples in this course.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><em fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Duration:</strong></strong></em><em fr-original-style="" style="box-sizing: border-box;"><em fr-original-style="" style="box-sizing: border-box;">&nbsp;3 Evenings, once per week for 3 weeks 6pm-8pm, of which the first date only shows on the booking.</em></em></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Virtual Classroom:&nbsp;</strong></strong>You could attend in our classroom, or attend online via virtual classroom, by select the appropriate ticket.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Who Should Attend?</strong></strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">This course is intended for beginner programmers who need to code in Python. Fast-paced, Quite intensive.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course Outline:</strong></strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Session&nbsp;</strong></strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">1: Basics</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Data Types, Variables,</strong></strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Operators and Expressions:</strong></strong>&nbsp;Arithmetic operators; Relational operators; Assignment operator; Logical operators.</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Decision Making:</strong></strong>&nbsp;If statement; If - else statement; If- elif - else statement; Nested if - else;</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Using Loops:</strong></strong>&nbsp;The while, while-else; do-while and the for loop; Enhanced for loop; Jump statements: break, continue; Nesting loops.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Session&nbsp;</strong></strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">2: Lists. Dictionaries, Json</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Python Data Structures: Lists. Data Structures: 2-d Lists, Tuples. Dictionary, Nested Disctionary.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Session&nbsp;</strong></strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">3: Built-in functions:</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Python Date Functions. Random. Math Functions. String Functions. Python Regex.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Session&nbsp;</strong></strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">4: Database:</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Connect to a database, create Database, create a table, insert, delete, update records, query a database and display results. Drop database, drop table.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Session&nbsp;</strong></strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">5: Files</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Exception Handling in Python<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">:&nbsp;</strong></strong>Fundamentals of exception handling; Exception types; Using try and except.</li><li fr-original-style="" style="box-sizing: border-box;">Files, streams: Create<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">,&nbsp;</strong></strong>Open, Traverse and Read Files: Csv, txt and Json Files.</li><li fr-original-style="" style="box-sizing: border-box;">API: Connecting to API&rsquo;s</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Session&nbsp;</strong></strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">6</strong></strong>:&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">M ethods, Classes and Objects</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Creating and using Function, Working with parameters, Calling functions.</li><li fr-original-style="" style="box-sizing: border-box;">Object-Oriented Programming (OOP) principles. Modules and Classes, Creating an Object; Using an Object; Adding Instance variables; Controlling accessibility; Naming conventions for class member.s</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><br fr-original-style="" style="box-sizing: border-box;"></p><div data-testid="image-content" fr-original-style="" style="box-sizing: border-box;"><img src="https://img.evbuc.com/https%3A%2F%2Fcdn.evbuc.com%2Fimages%2F447713699%2F44980801875%2F1%2Foriginal.20230216-130657?h=2000&w=720&auto=format%2Ccompress&q=75&sharp=10&s=c331eac85ab8cd495a7a46a3aa8c2b7b" alt="" data-airgap-id="86" fr-original-style="" style="cursor: pointer; padding: 0px 1px; user-select: none; max-width: 100%; position: relative; box-sizing: border-box;" fr-original-class="fr-draggable"></div><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">FAQ</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Do I need Python on my Laptop?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Ideally spoken yes, but if not possible, you could use our online platform.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Can I pay by BACS?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, simply email us, a Python course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Can I pay with PayPal?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, simply email us, a course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Do I get an invoice?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, on request.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Can I pay with a PO (Purchase Order Number)?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, simply email us, a Python course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Do I get a certificate?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, a PCWorkshops Certificate</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Can I attend in classroom?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, on request, and it would incur an additional charge, depending on your location. We have offices in London, Manchester, Birmingham, Portmouth, Southend-on-Sea, Milton Keynes.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Can beginners follow this course?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, this is a Python beginner friendly course. We offer Python courses with max 4 people, so we make sure each delegates fully understand the material covered</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Can I customise the course?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, all our Python courses are customisable. We can customise the dates, times, location. course outline.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"></p></div><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></p><div style="color: rgb(30, 10, 60); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(30, 10, 60);"><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><h2 fr-original-style="" style="box-sizing: border-box;">Refund Policy</h2></div><div style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">No Refunds</div>

Python coding, interactive, instructor-led, hands-on, practical. From basics to working with professionals. Python Part Time. Python Coding.



Python Beginners Evenings Course
Course summary
This Python Programming course has become essential to all professional who would like to do code using Python. Learn evenings, work while studying. Work and study Python Part Time.
It is a Python beginners course and teaches Python coding from scratch to intermediate.
Hands-on, practical. We code some real life examples in this course.
Duration: 4 Evenings, once per week for 34weeks 6pm-8pm, of which the first date only shows on the booking.
Virtual Classroom: You could attend in our classroom, or attend online via virtual classroom, by select the appropriate ticket.
Who Should Attend?
This course is intended for beginner programmers who need to code in Python. Fast-paced, Quite intensive.
Course Outline:
Session 1: Basics
Python Data Types, Variables,
Operators and Expressions: Arithmetic operators; Relational operators; Assignment operator; Logical operators.
Decision Making: If statement; If - else statement; If- elif - else statement; Nested if - else;
Using Loops: The while, while-else; do-while and the for loop; Enhanced for loop; Jump statements: break, continue; Nesting loops.
Session 2: Lists. Dictionaries, Json
Python Data Structures: Lists. Data Structures: 2-d Lists, Tuples. Dictionary, Nested Disctionary. API's. Exceptions and CSV Files
Session 3: Built-in functions:
Python Random. Math Functions. String Functions.
Database:
Connect to a database, query a database and display results. 
Session 4: Methods, Classes and Objects
Creating and using Function, Working with parameters, Calling functions.
Object-Oriented Programming (OOP) principles. Modules and Classes, Creating an Object; Using an Object; Adding Instance variables; Controlling accessibility; Naming conventions for class member.s



FAQ
Do I need Python on my Laptop?
Ideally spoken yes, but if not possible, you could use our online platform.
Can I pay by BACS?
Yes, simply email us, a Python course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com
Can I pay with PayPal?
Yes, simply email us, a course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com
Do I get an invoice?
Yes, on request.
Can I pay with a PO (Purchase Order Number)?
Yes, simply email us, a Python course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com
Do I get a certificate?
Yes, a PCWorkshops Certificate
Can I attend in classroom?
Yes, on request, and it would incur an additional charge, depending on your location. We have offices in London, Manchester, Birmingham, Portmouth, Southend-on-Sea, Milton Keynes.
Can beginners follow this course?
Yes, this is a Python beginner friendly course. We offer Python courses with max 4 people, so we make sure each delegates fully understand the material covered
Can I customise the course?
Yes, all our Python courses are customisable. We can customise the dates, times, location. course outline.






Refund Policy
No Refunds

Course summary



This Python Programming course has become essential to all professional who would like to do code using Python. Learn evenings, work while studying. Work and study Python Part Time.



It is a Python beginners course and teaches Python coding from scratch to intermediate.



Hands-on, practical. We code some real life examples in this course.



Python Programming Beginners Evenings Course, Virtual Classroom.

Keep 020 7164 6359 for your contact on the day. Thanks for booking!

Python Evenings in Classroom, London

<p><strong> Boost Your Career By Enrolling On This Python Course To Get Through Challenging Moments!</strong></p><p><em><strong>Become a Python programmer and study one of the most in-demand talents for employers in the upcoming year!</strong></em></p><p>This is the most extensive, but simple, Python programming language course available! This programming language course is for you whether you've never coded before, know basic grammar, or want to learn about Python's advanced techniques. You will learn the Python programming language course the way that suits you best!</p><p>This course is accredited by <strong>CPD </strong>with <strong>10 CPD points</strong> for professional development. Students can expect to complete this course in around <strong>09 hours</strong>. You'll also get dedicated expert assistance from us to answer any queries you may have while studying our course.</p><p>Upon successful completion of the Python course, an instant e-certificate will be exhibited in your profile that you can order as proof of your new skills and knowledge. Add these amazing new skills to your resume and boost your employability by simply enrolling in this course.</p><p>You'll get a <strong>Free Student ID</strong> card by enrolling in this course. This ID card entitles you to discounts on bus tickets, movie tickets, and library cards.</p><p>This course can help you to accomplish your ambitions and prepare you for a meaningful career. So, join the course today - gear up with the essential skills to set yourself up for excellence!</p><p><strong>What you will learn from this Course?</strong></p><ul><li>Become a skilled Developer</li><li>How to use the basic structures: strings, lists, and dictionaries</li><li>How to use Object-Oriented Programming (OOP)</li><li>How to use core programming tools such as functions and loops</li><li>How to land your first job as a Developer</li><li>write Python scripts to perform automated actions</li><li>Start creating your Python programs from scratch</li><li>Learn to use variables to store, retrieve and calculate information</li></ul><p><strong>Why should you choose this course with Academy for Health &amp; Fitness?</strong></p><ul><li>Opportunity to earn a certificate accredited by <strong>CPD </strong>after completing this course</li><li><strong>Student ID</strong> card with amazing discounts - completely for <strong> FREE!</strong> (£10 postal charges will be applicable for international delivery)</li><li>Globally accepted standard structured lesson planning</li><li>Innovative and engaging content and activities</li><li>Assessments that measure higher-level thinking and skills</li><li>Complete the program in your own time, at your own pace</li><li>Each of our students gets full 24/7 tutor support</li></ul> <p>With this comprehensive course, you can achieve your dreams and train for your ideal career. The Python course provides students with an in-depth learning experience that they can work through at their own pace to enhance their professional development.</p><p>Start your learning journey straight away with this course and take a step toward a brighter future!</p><p><strong>*** Course Curriculum ***</strong></p><p><strong></strong><strong> Learn Programming with Python Course</strong><strong></strong></p><p><strong>Module 01:</strong></p><ul><li>An Installing Python</li><li>Documentation</li><li>Command-Line</li><li>Variables</li><li>Simple Python Syntax</li><li>Keywords</li><li>Import-Module</li></ul><p><strong>Module 02:</strong></p><ul><li>Additional Topics</li><li>If Elif Else</li><li>Iterable</li><li>For</li><li>Loops in Python</li><li>Execute</li><li>Exceptions</li></ul><p><strong>Module 03:</strong></p><ul><li>Data Types</li><li>Number Types</li><li>More Number Types</li><li>Strings</li><li>More Strings</li><li>Files</li><li>Lists</li><li>Dictionaries</li><li>Tuples</li><li>Sets</li></ul><p><strong>Module 04:</strong></p><ul><li>Comprehensions</li><li>Definitions</li><li>Functions</li><li>Default Arguments</li><li>Doc Strings</li><li>Variadic Functions</li><li>Factorial</li></ul><p><strong>Module 05:</strong></p><ul><li>Function Objects</li><li>Lambda</li><li>Generators</li><li>Object Initialization</li><li>Class Static Members</li><li>Classic Inheritance</li><li>Data Hiding</li></ul><p><strong>Assessment Process</strong></p><p>Once you have completed all the modules in the Python course, your skills and knowledge will be tested with an automated multiple-choice assessment. You will then receive instant results to let you know if you have successfully passed the course.</p><p><strong>Show off Your New Skills with a Certificate of Completion</strong></p><p>The learners have to successfully complete the assessment of this Course to achieve the <strong>CPD accredited certificate.</strong> Digital certificates can be ordered for only £10. The learner can purchase printed hard copies inside the UK for £29, and international students can purchase printed hard copies for £39.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        10 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div> <h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>Anyone interested in learning more about the topic is advised to take this course. This course is open to everybody.</p>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You will not need any prior background or expertise to enrol in this course.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>After completing this course, you are to start your career or begin the next phase of your career.</p>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            £10
        </p>
        <h4>CPD Accredited Certificate </h4>
        <p>
            Hard copy certificate -
            £29
        </p>
            <div> <p>If you are an international student, then you have to pay an additional 10 GBP as an international delivery charge.</p> </div>

                        </div>

Boost Your Career By Enrolling On This Python Course To Get Through Challenging Moments!
Become a Python programmer and study one of the most in-demand talents for employers in the upcoming year!
This is the most extensive, but simple, Python programming language course available! This programming language course is for you whether you've never coded before, know basic grammar, or want to learn about Python's advanced techniques. You will learn the Python programming language course the way that suits you best!
This course is accredited by CPD with 10 CPD points for professional development. Students can expect to complete this course in around 09 hours. You'll also get dedicated expert assistance from us to answer any queries you may have while studying our course.
Upon successful completion of the Python course, an instant e-certificate will be exhibited in your profile that you can order as proof of your new skills and knowledge. Add these amazing new skills to your resume and boost your employability by simply enrolling in this course.
You'll get a Free Student ID card by enrolling in this course. This ID card entitles you to discounts on bus tickets, movie tickets, and library cards.
This course can help you to accomplish your ambitions and prepare you for a meaningful career. So, join the course today - gear up with the essential skills to set yourself up for excellence!
What you will learn from this Python Course?
Become a skilled Developer
How to use the basic structures: strings, lists, and dictionaries
How to use Object-Oriented Programming (OOP)
How to use core programming tools such as functions and loops
How to land your first job as a Developer
write Python scripts to perform automated actions
Start creating your Python programs from scratch
Learn to use variables to store, retrieve and calculate information
Why should you choose this course with Academy for Health & Fitness?
Opportunity to earn a certificate accredited by CPD after completing this course
Student ID card with amazing discounts - completely for FREE! (£10 postal charges will be applicable for international delivery)
Globally accepted standard structured lesson planning
Innovative and engaging content and activities
Assessments that measure higher-level thinking and skills
Complete the program in your own time, at your own pace
Each of our students gets full 24/7 tutor support
With this comprehensive course, you can achieve your dreams and train for your ideal career. The Python course provides students with an in-depth learning experience that they can work through at their own pace to enhance their professional development.



Start your learning journey straight away with this Python course and take a step toward a brighter future!
*** Course Curriculum ***
Learn Programming with Python Course
Module 01:
An Installing Python
Documentation
Command-Line
Variables
Simple Python Syntax
Keywords
Import-Module
Module 02:
Additional Topics
If Elif Else
Iterable
For
Loops in Python
Execute
Exceptions
Module 03:
Data Types
Number Types
More Number Types
Strings
More Strings
Files
Lists
Dictionaries
Tuples
Sets
Module 04:
Comprehensions
Definitions
Functions
Default Arguments
Doc Strings
Variadic Functions
Factorial
Module 05:
Function Objects
Lambda
Generators
Object Initialization
Class Static Members
Classic Inheritance
Data Hiding
Assessment Process
Once you have completed all the modules in the Python course, your skills and knowledge will be tested with an automated multiple-choice assessment. You will then receive instant results to let you know if you have successfully passed the course.
Show off Your New Skills with a Certificate of Completion
The learners have to successfully complete the assessment of this Course to achieve the CPD accredited certificate. Digital certificates can be ordered for only £10. The learner can purchase printed hard copies inside the UK for £29, and international students can purchase printed hard copies for £39.
CPD 
10 CPD hours / points  Accredited by CPD Quality Standards



Who is this course for? 
Anyone interested in learning more about the topic is advised to take this Python course. This course is open to everybody.



Requirements 
You will not need any prior background or expertise to enrol in this Python course.



Career path
After completing this Python course, you are to start your career or begin the next phase of your career.



Certificates 
Certificate of completion
Digital certificate - £10 
CPD Accredited Certificate
Hard copy certificate - £29 
If you are an international student, then you have to pay an additional 10 GBP as an international delivery charge.

Academy for Health and Fitness

Assessment Practising Certificate (APC)

Continuous Professional Development (CPD)

Python - CPD Accredited

<article>
<div>
<h5>Java Course 1 hour. Code the Hangman</h5>
</div>
<div></div>
<p>  						 
	</p><div>
	<ul>
		<p>
		<b>Python Course, code the Hangman. </b>Basic Python Course covers in one hour the coding of an interesting app. 
		<br />Any one very welcome.  
		<br /><b>Our Style: </b>Hands-on, Practical  
		<br /><b>Location:  </b>Online, Instructor-led  
		<br /><b>Download:  </b>anaconda.com
		<br /><b>Duration:  </b>1 Hour
		<br /><b>Times: </b>arrange a time for your time zone
	    </p>
	</ul>	

<p></p>
</div></article>

<div>
	  <div>
		 <h5>Python Basics Course Description</h5>
	  </div>
	  <div></div>
	  <p> Learn to code the Hangman Game in 1 hour. 
		<br /> Essentials of Python programming, explaining Python technology. 
		<br /> Practical Python lessons and Python exercises. 
		<br /> Great Tutors. 
		<br /> Online. 
		<br /> Learn plenty in one day: Code The Hangman Game in Python
	  </p>
	<div>
	<h5>Code the Hangman Game</h5>
	</div>
	<div></div>
	<div> 
		<p>  <strong>Python Course 1 Hour:</strong>  
		<br />  	STEP 1: Using variables. Arithmetic operations. Strings. String Functions
		<br />  	STEP 2: Getting user input from console. Decision Making (If-else).
		<br />  	STEP 3: For and While Loops. Repeat code by using loops.
		<br />  	STEP 4: Lists: Create, Update, Iterate Lists. Using indexes to refer to individual values.
		<br />  	STEP 5: Object Oriented Programming: Functions. Classes.  
		<br />  	STEP 6: Create the Hangman Game.			
		</p>
	</div>
 
</div>
 

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		  <div>
			 <h5>What is included with The Python Course 1 Hour</h5>
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		  <article>
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			 <ul>
				<li>PCWorkshops Python Course Certificate on completion  </li> 
				<li>Python Course Notes</li>
				<li>Python Code Examples</li>
				<li>Practical Python Course exercises and Code Samples</li>
				<li>After the course: 1-Hour personalised online revision session</li>
			 </ul>
		  </div>
		  </article>
	   </div>
				    
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	                  <div>
	                     <h5 id="cincluded2">Book the Python Course 1 hour</h5>
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	                     <h5>About us</h5>
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					    			<h5>Our experienced trainers are award winners. </h5> 
					    			<ul>
										<li>
											More about us
										</li>
										<li>
											FAQ's
										</li>
										<li>
											Client Comments  
										</li>
									 </ul>
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Java Course 1 hour. Code the Hangman
Online, Instructor-led
 
 Python Course, code the Hangman. Basic Python Course covers in one hour the coding of an interesting app. 
Any one very welcome. 
Our Style: Hands-on, Practical 

Location: Online, Instructor-led 
Download: anaconda.com 
Duration: 1 Hour 
Times: arrange a time for your time zone 
Python Basics Course Description
 Learn to code the Hangman Game in 1 hour. 
 Essentials of Python programming, explaining Python technology. 
 Practical Python lessons and Python exercises. 
 Great Tutors. 
 Online. 
 Learn plenty in one day: Code The Hangman Game in Python 
Code the Hangman Game
 Python Course 1 Hour: 
 STEP 1: Using variables. Arithmetic operations. Strings. String Functions 
 STEP 2: Getting user input from console. Decision Making (If-else). 
 STEP 3: For and While Loops. Repeat code by using loops. 
 STEP 4: Lists: Create, Update, Iterate Lists. Using indexes to refer to individual values. 
 STEP 5: Object Oriented Programming: Functions. Classes. 
 STEP 6: Create the Hangman Game. 
What is included with The Python Course 1 Hour
PCWorkshops Python Course Certificate on completion
Python Course Notes
Python Code Examples
Practical Python Course exercises and Code Samples
After the course: 1-Hour personalised online revision session
Book the Python Course 1 hour
About us
Our experienced trainers are award winners.
More about us
FAQ's
Client Comments

Application Software

Computing & Software Development Tools

Coding For Kids

Remote Desktop Software

Software Development

Python Course, code the Hangman. Basic Python Course covers in one hour the coding of an interesting app. 
Any one very welcome. 
Our Style: Hands-on, Practical 
Location: Online, Instructor-led 
Download: anaconda.com 
Duration: 1 Hour 
Times: arrange a time for your time zone 

Python Taster, Code the Hangman, Online Instrcutor-led 

<div style="color: rgb(57, 54, 79); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(57, 54, 79);"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Powerful 1-hour Python workshop course understand Python Basics. Practical. Instructor-led. Online.</strong></p></div><div data-testid="organizerBrief" fr-original-style="" style="box-sizing: border-box;"><div data-testid="creator-signal-main-section" fr-original-style="" style="box-sizing: border-box;"><section fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></section></div></div></div><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><h1 style="color: rgb(57, 54, 79); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(57, 54, 79);">Learn to code a Password Validator in 1 hour.&nbsp;</h1><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Basics made simple! &nbsp;Learn plenty in one day: Code A Password Validator</p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Essentials of Python programming.</li><li fr-original-style="" style="box-sizing: border-box;">Practical lessons and exercises.</li><li fr-original-style="" style="box-sizing: border-box;">Great Tutors.&nbsp;</li><li fr-original-style="" style="box-sizing: border-box;">Online.</li><li fr-original-style="" style="box-sizing: border-box;">You may Request a Central London Location, per email</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Who will the Course Benefit?</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">This is a fantastic course for beginners</li><li fr-original-style="" style="box-sizing: border-box;">Or for coders, simply fast-track crossing over to Python.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Teaching Style:&nbsp;</strong>Practical, Interactive, Personalised. Useful examples.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">What is included?</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Course notes, exercises and examples.</li><li fr-original-style="" style="box-sizing: border-box;">Course certificate.</li></ul><h2 style="color: rgb(30, 10, 60); box-sizing: border-box;" fr-original-style=" color: rgb(30, 10, 60);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Learn Python by coding a Password Validator</strong></h2><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">STEP 1:&nbsp;</strong>Using variables. Arithmetic operations. Strings. String Functions</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">STEP 2:&nbsp;</strong>Getting user input from console. Decision Making(If-else)</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">STEP 3:&nbsp;</strong>For and While Loops. Repeat code by using loops.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">STEP 4:&nbsp;</strong>Lists: Create, Update, Iterate Lists. Using indexes to refer to individual values.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">STEP 5:&nbsp;</strong>Object Oriented Programming. Functions. Classes.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">STEP 6:&nbsp;</strong>Create the Password Validator</p></div><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></p><div style="color: rgb(30, 10, 60); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(30, 10, 60);"><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><h2 fr-original-style="" style="box-sizing: border-box;">Refund Policy</h2></div><div style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">No Refunds</div>

Powerful 1-hour Python workshop course understand Python Basics. Practical. Instructor-led. Online.



Learn to code a Password Validator in 1 hour. 
Basics made simple! Learn plenty in one day: Code A Password Validator
Essentials of Python programming.
Practical lessons and exercises.
Great Tutors.
Online.
You may Request a Central London Location, per email
Who will the Course Benefit?
This is a fantastic course for beginners
Or for coders, simply fast-track crossing over to Python.
Teaching Style: Practical, Interactive, Personalised. Useful examples.
What is included?
Course notes, exercises and examples.
Course certificate.
Learn Python by coding a Password Validator
STEP 1: Using variables. Arithmetic operations. Strings. String Functions
STEP 2: Getting user input from console. Decision Making(If-else)
STEP 3: For and While Loops. Repeat code by using loops.
STEP 4: Lists: Create, Update, Iterate Lists. Using indexes to refer to individual values.
STEP 5: Object Oriented Programming. Functions. Classes.
STEP 6: Create the Password Validator





Refund Policy
No Refunds

Online Course Marketing

Powerful 1-hour Python workshop course understand Python Basics. Practical. Instructor-led. Online.
Learn to code a Password Validator in 1 hour. 



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