1899 Exercises courses in Leeds delivered On Demand

Welcome to the Qualifying Sales Course, where you will gain the essential skills and knowledge to become a successful sales professional. In this comprehensive program, you will learn how to identify and prioritize promising leads, ensuring that your sales efforts are focused on prospects with genuine potential. Through practical exercises and real-world scenarios, you will develop the expertise to qualify leads effectively, increase conversion rates, and ultimately boost your sales performance. Join us on this journey to master the art of qualifying sales, and take your career to new heights!

🌟 Unlock the Power of Information Management with 'Information Overload - Surplus of Data, Deficit of Time' Course! 🌟   Are you drowning in a sea of information but struggling to stay afloat with limited time? The digital age has blessed us with an abundance of data, yet mastering how to harness this information efficiently remains a challenge. ⏳ Time is your most valuable asset, and this course is your key to mastering the art of managing information overload!     🚀 Our comprehensive course offers: Strategies for Efficient Information Processing: Learn techniques to sift through the surplus of data swiftly and extract the most relevant insights without getting overwhelmed. Productivity Hacks for Time Optimization: Discover time-saving methods and tools to streamline your workflow, allowing you to make the most of your precious time. Effective Organization and Prioritization Techniques: Gain insights into organizing information effectively and prioritizing tasks to maximize productivity without sacrificing quality. Mindfulness and Stress Management in Information Handling: Understand how to maintain a healthy balance and reduce stress while navigating through the data deluge. Practical Exercises and Real-Life Scenarios: Apply learned strategies through hands-on exercises and real-world scenarios to solidify your understanding and implementation.   🎓 Taught by industry experts with years of experience in information management, this course equips you with the skills needed to conquer information overload, empowering you to thrive in today's data-driven world. 🌐 Join a community of like-minded individuals and embark on a journey to master the art of handling information overload effectively! Course Curriculum Module- 1 00:00 Module- 2 00:00 Module- 3 00:00 Module- 4 00:00 Module- 5 00:00 Module- 6 00:00 Module- 7 00:00 Module- 8 00:00 Module- 9 00:00 Module- 10 00:00

CPD Accredited | Career Oriented Learning Modules | 24x7 Tutor Support | Lifetime Access

Are you ready to be at the helm, steering the ship into a realm where data is the new gold? In the infinite world of data, where information spirals at breakneck speed, lies a universe rich in potential and discovery: the domain of Data Science and Visualisation. This 'Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3' course unravels the wonders of extracting meaningful insights using Python, the worldwide leading language of data experts. Harnessing the strength of Python, you'll delve deep into data analysis, experience the finesse of visualisation tools, and master the art of Machine Learning. The need to understand, interpret, and act on this data has become paramount, with vast amounts of data increasing the digital sphere. Envision a canvas where raw numbers are transformed into visually compelling stories, and machine learning models foretell future trends. This course provides a meticulous pathway for anyone eager to learn the data representation paradigms backed by Python's robust libraries. Dive into a curriculum rich with analytical explorations, visual artistry, and machine learning predictions. Learning Outcomes Understanding the foundations and functionalities of Python, focusing on its application in data science. Applying various Python libraries like NumPy and Pandas for effective data analysis. Demonstrating proficiency in creating detailed visual narratives using tools like matplotlib, Seaborn, and Plotly. Implementing Machine Learning algorithms in Python using scikit-learn, ranging from regression models to clustering techniques. Designing and executing a holistic data analysis and visualisation project, encapsulating all learned techniques. Exploring advanced topics, encompassing recommender systems and natural language processing with Python. Attaining the confidence to independently analyse complex data sets and translate them into actionable insights.   Video Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/Data-Science-and-Visualisation-with-Machine-Learning.mp400:0000:0000:00Use Up/Down Arrow keys to increase or decrease volume. Why buy this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Who is this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 course for? Aspiring data scientists aiming to harness the power of Python. Researchers keen to enrich their analytical and visualisation skills. Analysts aiming to add machine learning to their toolkit. Developers striving to integrate data analytics into applications. Business professionals desiring data-driven decision-making capabilities. Career path Data Scientist: £55,000 - £85,000 Per Annum Machine Learning Engineer: £60,000 - £90,000 Per Annum Data Analyst: £30,000 - £50,000 Per Annum Data Visualisation Specialist: £45,000 - £70,000 Per Annum Natural Language Processing Specialist: £65,000 - £95,000 Per Annum Business Intelligence Developer: £40,000 - £65,000 Per Annum Prerequisites This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £85 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview 00:07:00 Set-up the Environment for the Course (lecture 1) 00:09:00 Set-up the Environment for the Course (lecture 2) 00:25:00 Two other options to setup environment 00:04:00 Python Essentials Python data types Part 1 00:21:00 Python Data Types Part 2 00:15:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00 Python Essentials Exercises Overview 00:02:00 Python Essentials Exercises Solutions 00:22:00 Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. 00:03:00 NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes. 00:28:00 NumPy Essentials - Indexing, slicing, broadcasting & boolean masking 00:26:00 NumPy Essentials - Arithmetic Operations & Universal Functions 00:07:00 NumPy Essentials Exercises Overview 00:02:00 NumPy Essentials Exercises Solutions 00:25:00 Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. 00:02:00 Pandas Introduction 00:02:00 Pandas Essentials - Pandas Data Structures - Series 00:20:00 Pandas Essentials - Pandas Data Structures - DataFrame 00:30:00 Pandas Essentials - Handling Missing Data 00:12:00 Pandas Essentials - Data Wrangling - Combining, merging, joining 00:20:00 Pandas Essentials - Groupby 00:10:00 Pandas Essentials - Useful Methods and Operations 00:26:00 Pandas Essentials - Project 1 (Overview) Customer Purchases Data 00:08:00 Pandas Essentials - Project 1 (Solutions) Customer Purchases Data 00:31:00 Pandas Essentials - Project 2 (Overview) Chicago Payroll Data 00:04:00 Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00 Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach 00:13:00 Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials - Exercises Overview 00:06:00 Matplotlib Essentials - Exercises Solutions 00:21:00 Python for Data Visualization using Seaborn Seaborn - Introduction & Installation 00:04:00 Seaborn - Distribution Plots 00:25:00 Seaborn - Categorical Plots (Part 1) 00:21:00 Seaborn - Categorical Plots (Part 2) 00:16:00 Seborn-Axis Grids 00:25:00 Seaborn - Matrix Plots 00:13:00 Seaborn - Regression Plots 00:11:00 Seaborn - Controlling Figure Aesthetics 00:10:00 Seaborn - Exercises Overview 00:04:00 Seaborn - Exercise Solutions 00:19:00 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1) 00:19:00 Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2) 00:14:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview) 00:11:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions) 00:37:00 Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) 00:15:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00 Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) 00:03:00 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types.. 00:15:00 Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00 scikit-learn - Linear Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Linear Regression Model Hands-on (Part 2) 00:19:00 Good to know! How to save and load your trained Machine Learning Model! 00:01:00 scikit-learn - Linear Regression Model (Insurance Data Project Overview) 00:08:00 scikit-learn - Linear Regression Model (Insurance Data Project Solutions) 00:30:00 Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc. 00:10:00 scikit-learn - Logistic Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Logistic Regression Model - Hands-on (Part 2) 00:20:00 scikit-learn - Logistic Regression Model - Hands-on (Part 3) 00:11:00 scikit-learn - Logistic Regression Model - Hands-on (Project Overview) 00:05:00 scikit-learn - Logistic Regression Model - Hands-on (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality . 00:08:00 scikit-learn - K Nearest Neighbors - Hands-on 00:25:00 scikt-learn - K Nearest Neighbors (Project Overview) 00:04:00 scikit-learn - K Nearest Neighbors (Project Solutions) 00:14:00 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging. 00:18:00 scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1) 00:19:00 scikit-learn - Decision Tree and Random Forests (Project Overview) 00:05:00 scikit-learn - Decision Tree and Random Forests (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) 00:07:00 scikit-learn - Support Vector Machines - Hands-on (SVMs) 00:30:00 scikit-learn - Support Vector Machines (Project 1 Overview) 00:07:00 scikit-learn - Support Vector Machines (Project 1 Solutions) 00:20:00 scikit-learn - Support Vector Machines (Optional Project 2 - Overview) 00:02:00 Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method .. 00:11:00 scikit-learn - K Means Clustering - Hands-on 00:23:00 scikit-learn - K Means Clustering (Project Overview) 00:07:00 scikit-learn - K Means Clustering (Project Solutions) 00:22:00 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) 00:09:00 scikit-learn - Principal Component Analysis (PCA) - Hands-on 00:22:00 scikit-learn - Principal Component Analysis (PCA) - (Project Overview) 00:02:00 scikit-learn - Principal Component Analysis (PCA) - (Project Solutions) 00:17:00 Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance 00:06:00 Python for Recommender Systems - Hands-on (Part 1) 00:18:00 Python for Recommender Systems - - Hands-on (Part 2) 00:19:00 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) 00:13:00 NLTK - NLP-Challenges, Data Sources, Data Processing .. 00:13:00 NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00 NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW. 00:19:00 NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes 00:13:00 NLTK - NLP - Pipeline feature to assemble several steps for cross-validation 00:09:00 Resources Resources - Data Science and Visualisation with Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

ISO 31000:2018 is an international standard of Risk Management, the existence of it requires competent personnel to interpret its guidelines, address those to integrate Risk Management in an organization’s operations and audit organization to assess the implementation and effectiveness of overall implementation. This course is designed for professionals who are responsible of any aspect of Risk Management as well as for those, specifically, who are pursuing their career in the field of auditing Risk Management. This course enhances the knowledge and skills of delegates to understand the standard and audit it effectively. Course is consisting of study material in form of written details. Attendees of this course will be, on completion, competent to implement Risk Management, Plan, Conduct & Report 1st, 2nd & 3rd party audits. This course also discusses about different risk assessment techniques such as Brainstorming Structured or semi-structured interviews Delphi technique Check-lists Preliminary hazard analysis (PHA) HAZOP Hazard analysis and critical control points (HACCP) Toxicity assessment Structured “What-if” Technique (SWIFT) Scenario analysis Business impact analysis (BIA) Root cause analysis (RCA) Failure modes and effects analysis (FMEA) and failure modes and effects and criticality analysis (FMECA) Fault tree analysis (FTA) Event tree analysis (ETA) Cause-consequence analysis Cause-and-effect analysis Layers of protection analysis (LOPA) Decision tree analysis Human reliability assessment (HRA) Bow tie analysis Reliability centred maintenance Sneak analysis (SA)and sneak circuit analysis (SCI) Markov analysis Monte Carlo simulation Bayesian statistics and Bayes Nets FN curves Risk indices Consequence/ probability matrix Cost/benefit analysis (CBA) Multi-criteria decision analysis (MCDA)   Features of Couse ✔ 100% Online Self-paced: Considering the busy lives, we have designed this course to be attended online without bounding with the schedules. To make it interactive, we have created different communication groups where candidate can discuss the points with other fellows as well as the trainers of course. ✔ Testing the Learning: Each section of course is covered with exercise to check your knowledge in real-time, and overall result is affected by exercises you complete. ✔ Self-Scheduling: This 40 Hours full fledge course is designed to match you schedule. You will get a life time access to this course and complete it on your ease. ✔ Superlative Material: The training is designed, developed and reviewed by competent auditors having an extensive experience of auditing in different regions of world. ✔ Approved Course: The course is approved by one of the well-known personal certifying body “IRCP”.   Who should attend this? This course is recommended to be attended by those who are involved in implementation and/ or auditing of Risk Management System, specifically Risk Managers, Auditors and others willing to add credibility with a widely accepted qualification for auditing. Also, recommended to satisfy the applicable requirement of training and competence, if any. This course can add values to your profile if you are Intending to perform audits of RM. A Risk Management Executive/ Management Representative An Existing Internal Auditor A Ris Management Consultant Responsible for implementing the ISO 31000 standard. Responsibility to evaluate the outcome of internal RM audits and have responsibility/ authority to improve the effectiveness of the RM. Pursuing to make career in RM auditing.   Course Duration: 40 Learning Hours and extended time of exercise & Exam.   Certificate: Those who pass all exercises with 50% at least in each exercise and 70% overall marks will be awarded with successfully completion certificate with approval of Exemplar Global and a Lifetime validity.   Language of Course: English   Pre-Requisites: Knowledge of Risk Management

🌟 Unleash Your True Potential with 'Being Present and Owning Yourself' Online Course! 🌟   Are you ready to embark on a transformative journey towards a more fulfilling and empowered life? Say goodbye to autopilot living and embrace the art of being present! Introducing our revolutionary online course:   🌈 Being Present and Owning Yourself: A Path to Authentic Living 🌈   ✨ What's Inside?   🧘 Mindful Mastery: Learn powerful techniques to bring mindfulness into your daily life, fostering a deep connection with the present moment. Discover how being fully present can alleviate stress, enhance focus, and cultivate a sense of inner peace.   💪 Empowerment Blueprint: Uncover the keys to owning your narrative and reclaiming your personal power. Dive into self-discovery exercises and strategies that empower you to live life on your terms.   🌟 Authenticity Unleashed: Explore the art of authenticity and the freedom that comes with embracing your true self. Break free from societal expectations and unlock the door to a more genuine and fulfilling existence.   🚀 Practical Applications: This course isn't just theoretical; it's a hands-on guide to integrating these transformative practices into your daily routine. Realize immediate and tangible benefits as you apply the lessons in real-life scenarios.   🎓 Expert Guidance: Join a community of like-minded individuals on this journey, guided by experts in mindfulness, personal development, and authenticity. Benefit from their wisdom, ask questions, and share your experiences along the way.   🎁 Exclusive Bonuses: Guided Meditations: Access a library of soothing meditations designed to enhance your mindfulness practice. Interactive Workbooks: Dive deeper into the material with downloadable workbooks and exercises. Live Q&A Sessions: Get the chance to interact with the course instructors and receive personalized guidance.   🌟 Why Wait? Seize Your Transformation Today!   Invest in yourself and take the first step towards a life filled with purpose, authenticity, and joy. Don't let another moment pass you by - enroll in 'Being Present and Owning Yourself' now!   🌐 Limited-Time Offer: Enroll today and receive an exclusive discount. Your journey to a more present and empowered self starts here!   ✨ Embrace the present. Own your story. Transform your life. ✨ Course Curriculum

You Design Think More Than You Know Today's world is very volatile, uncertain, complex and ambiguous. What used to work, seems to work less efficient or effective. The pandemic shows us that the consequences in daily life can be huge. For some of us, this means confusion and struggle to find solutions to problems. Others reflect on what is happening and reframe this VUCA world as an opportunity for creating new products, services of systems. Start to think as a designer. Designing solutions serves users and customers. Real human beings with names, moods, needs and problems. We sometimes forget, because while creating solutions we fall in love with them. Our attention focuses on the solution. Design thinking has made empathizing with the customer one of the main anchor points. You always remember for whom you are designing and creating. How many ideas would you need to find the one that fits the problem of your user? Ten, a hundred or maybe more? The answer is, more than you think now. Start with questioning the problem. Play and collect different perspectives on the problem. Every single perspective leads to different ideas. In this way you easily reach a great number of solutions. We will share a few relevant, creative exercises so you can challenge your own dominant reaction to solving problems. Having this personal experience will help you to adopt a design thinking mindset to help your clients. What You Will Learn: Introduction to Design Thinking Two Exercises to change your perspectives on problems and solutions Reflection on one's own thinking system How to reframe constraints as valuable opportunities to find creative solutions

Lean Six Sigma Yellow Belt Certification Program - Build a Knowledge Base of the Facets of Lean Six Sigma: On-Demand This course is designed to teach you the fundamental concepts of Lean Six Sigma and enable you to achieve IIL's Lean Six Sigma Yellow Belt Certification. The Lean Six Sigma methodology is focused on improving business performance, reducing costs, and increasing efficiency and productivity. In this course, you'll get an introduction to what Lean Six Sigma is about, including its vision, key metrics, and the DMAIC process (Define, Measure, Analyze, Improve, Control) which is the foundation of Lean Six Sigma and the de facto tool for process improvement. Improved processes result in higher quality, lower costs, and increased customer satisfaction! Benefits of Lean Six Sigma Gives leadership a standard, data-driven approach to improving results Gives project managers a set of understandable steps and tools to improve project effectiveness Generates higher net income by lowering operating costs Improves product and service quality through defect prevention and reduction Improves customer satisfaction and retention by identifying and meeting customer requirements Improves employee satisfaction by reducing rework What You Will Learn You will learn how to: Establish the structure that supports and sustains Lean Six Sigma Quality Identify and calculate key Lean Six Sigma Measurements (Sigma, DPMO and Yield) Select successful, high-impact projects that match to strategic objectives Document, measure and improve key processes using the DMAIC (Define, Measure, Analyze, Improve and Control) Methodology Utilize data-based thinking to make key business decisions Day One or eLearning Session One and Two: Introduction to the Fundamentals and Vision of Lean Six Sigma. Topics include: Lean Six Sigma's focus on the customer, on quality, and on results The costs of poor quality Critical factors to consider when deploying Lean Six Sigma Lean Six Sigma as a process improvement methodology Lean Six Sigma metrics Why do it - ROI and payback for Lean Six Sigma Business Process Management Critical Lean Six Sigma roles and responsibilities Main aspects of managing the organizational change Project selection Day Two or eLearning Session Two, Three, and Four: Metrics of Lean Six Sigma and the DMAIC Model. This part of the course will focus on the systematic and proven use of the Define, Measure, Analyze, Improve, and Control (DMAIC) Methodology to dramatically reduce current process defects. Participants will practice using the common tools and techniques behind each phase through interactive exercises. Topics include: How to strategically align business metrics and projects within an organization How to identify and measure quality characteristics which are critical to customers What does the customer (internal or external) really want from our products and services? Establishing appropriate teams and setting those teams up to be successful What defines a good measurement system? How are we doing (learning the secret to measuring the right things, right)? How to improve output measures by understanding and measuring the process Where are there defects (how to properly select and scope high-impact projects)? Where is the process broken (the Lean Six Sigma version of root cause analysis)? How to determine the process efficiency, or value add, of a process The appropriate use of quality tools Understanding the concept of variation and how to reduce knee-jerk reactions How to achieve breakthrough results for any key measure How can we ensure the identified improvements will be sustainable (the basics of process control)?

Learning Outcomes After completing this course, learners will be able to: Learn Python for data analysis using NumPy and Pandas Acquire a clear understanding of data visualisation using Matplotlib, Seaborn and Pandas Deepen your knowledge of Python for interactive and geographical potting using Plotly and Cufflinks Understand Python for data science and machine learning Get acquainted with Recommender Systems with Python Enhance your understanding of Python for Natural Language Processing (NLP) Description Whether you are from an engineering background or not you still can efficiently work in the field of data science and the machine learning sector, if you have proficient knowledge of Python. Since Python is the easiest and most used programming language, you can start learning this language now to advance your career with the Data Science And Machine Learning Using Python : A Bootcamp course. This course will give you a thorough understanding of the Python programming language. Moreover, it will show how can you use Python for data analysis and machine learning. Alongside that, from this course, you will get to learn data visualisation, and interactive and geographical plotting by using Python. The course will also provide detailed information on Python for data analysis, Natural Language Processing (NLP) and much more. Upon successful completion of this course, get a CPD- certificate of achievement which will enhance your resume and career. Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post.  Method of Assessment After completing this course, you will be provided with some assessment questions. To pass that assessment, you need to score at least 60%. Our experts will check your assessment and give you feedback accordingly. Career Path After completing this course, you can explore various career options such as Web Developer Software Engineer Data Scientist Machine Learning Engineer Data Analyst In the UK professionals usually get a salary of £25,000 - £30,000 per annum for these positions. Course Content Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview 00:07:00 Set-up the Environment for the Course (lecture 1) 00:09:00 Set-up the Environment for the Course (lecture 2) 00:25:00 Two other options to setup environment 00:04:00 Python Essentials Python data types Part 1 00:21:00 Python Data Types Part 2 00:15:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00 Python Essentials Exercises Overview 00:02:00 Python Essentials Exercises Solutions 00:22:00 Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. 00:03:00 NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes. 00:28:00 NumPy Essentials - Indexing, slicing, broadcasting & boolean masking 00:26:00 NumPy Essentials - Arithmetic Operations & Universal Functions 00:07:00 NumPy Essentials Exercises Overview 00:02:00 NumPy Essentials Exercises Solutions 00:25:00 Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. 00:02:00 Pandas Introduction 00:02:00 Pandas Essentials - Pandas Data Structures - Series 00:20:00 Pandas Essentials - Pandas Data Structures - DataFrame 00:30:00 Pandas Essentials - Handling Missing Data 00:12:00 Pandas Essentials - Data Wrangling - Combining, merging, joining 00:20:00 Pandas Essentials - Groupby 00:10:00 Pandas Essentials - Useful Methods and Operations 00:26:00 Pandas Essentials - Project 1 (Overview) Customer Purchases Data 00:08:00 Pandas Essentials - Project 1 (Solutions) Customer Purchases Data 00:31:00 Pandas Essentials - Project 2 (Overview) Chicago Payroll Data 00:04:00 Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00 Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach 00:13:00 Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials - Exercises Overview 00:06:00 Matplotlib Essentials - Exercises Solutions 00:21:00 Python for Data Visualization using Seaborn Seaborn - Introduction & Installation 00:04:00 Seaborn - Distribution Plots 00:25:00 Seaborn - Categorical Plots (Part 1) 00:21:00 Seaborn - Categorical Plots (Part 2) 00:16:00 Seborn-Axis Grids 00:25:00 Seaborn - Matrix Plots 00:13:00 Seaborn - Regression Plots 00:11:00 Seaborn - Controlling Figure Aesthetics 00:10:00 Seaborn - Exercises Overview 00:04:00 Seaborn - Exercise Solutions 00:19:00 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1) 00:19:00 Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2) 00:14:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview) 00:11:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions) 00:37:00 Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) 00:15:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00 Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) 00:03:00 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types.. 00:15:00 Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00 scikit-learn - Linear Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Linear Regression Model Hands-on (Part 2) 00:19:00 Good to know! How to save and load your trained Machine Learning Model! 00:01:00 scikit-learn - Linear Regression Model (Insurance Data Project Overview) 00:08:00 scikit-learn - Linear Regression Model (Insurance Data Project Solutions) 00:30:00 Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc. 00:10:00 scikit-learn - Logistic Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Logistic Regression Model - Hands-on (Part 2) 00:20:00 scikit-learn - Logistic Regression Model - Hands-on (Part 3) 00:11:00 scikit-learn - Logistic Regression Model - Hands-on (Project Overview) 00:05:00 scikit-learn - Logistic Regression Model - Hands-on (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality . 00:08:00 scikit-learn - K Nearest Neighbors - Hands-on 00:25:00 scikt-learn - K Nearest Neighbors (Project Overview) 00:04:00 scikit-learn - K Nearest Neighbors (Project Solutions) 00:14:00 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging. 00:18:00 scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1) 00:19:00 scikit-learn - Decision Tree and Random Forests (Project Overview) 00:05:00 scikit-learn - Decision Tree and Random Forests (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) 00:07:00 scikit-learn - Support Vector Machines - Hands-on (SVMs) 00:30:00 scikit-learn - Support Vector Machines (Project 1 Overview) 00:07:00 scikit-learn - Support Vector Machines (Project 1 Solutions) 00:20:00 scikit-learn - Support Vector Machines (Optional Project 2 - Overview) 00:02:00 Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method .. 00:11:00 scikit-learn - K Means Clustering - Hands-on 00:23:00 scikit-learn - K Means Clustering (Project Overview) 00:07:00 scikit-learn - K Means Clustering (Project Solutions) 00:22:00 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) 00:09:00 scikit-learn - Principal Component Analysis (PCA) - Hands-on 00:22:00 scikit-learn - Principal Component Analysis (PCA) - (Project Overview) 00:02:00 scikit-learn - Principal Component Analysis (PCA) - (Project Solutions) 00:17:00 Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance 00:06:00 Python for Recommender Systems - Hands-on (Part 1) 00:18:00 Python for Recommender Systems - - Hands-on (Part 2) 00:19:00 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) 00:13:00 NLTK - NLP-Challenges, Data Sources, Data Processing .. 00:13:00 NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00 NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW. 00:19:00 NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes 00:13:00 NLTK - NLP - Pipeline feature to assemble several steps for cross-validation 00:09:00 Resources Resources - Data Science and Machine Learning using Python : A Bootcamp 00:00:00 Order your Certificates & Transcripts Order your Certificates & Transcripts 00:00:00 Frequently Asked Questions Are there any prerequisites for taking the course? 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. Can I access the course at any time, or is there a set schedule? 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. How long will I have access to the course? 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. Is there a certificate of completion provided after completing the course? 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. Can I switch courses or get a refund if I'm not satisfied with the course? 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. How do I track my progress in the course? 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. What if I have technical issues or difficulties with the course? 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.

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