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Register on the Python Data Science 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. 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. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a digital certificate as a proof of your course completion. The Python Data Science 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. 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! What You Get With The Python Data Science Receive a e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Course Design 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. You are taught through a combination of Video lessons Online study materials Certification 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. Who Is This Course For: 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. Requirements: The online training is open to all students and has no formal entry requirements. To study the Python Data Science, 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. Course Content Unit 01: Introduction to Python Data Science Module 01: Introduction to Python Data Science 00:03:00 Module 02: Environment Setup 00:10:00 Unit 02: Data Cleaning Packages Module 01: Numpy package for calculations 00:16:00 Module 02: Panda package for Data cleaning 00:19:00 Unit 03: Data Visualization packages Module 01: Matplotlib Data Visualization Part 1 00:16:00 Module 02: Matplotlib Data Visualization Part 2 00:11:00 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.
Dive into the captivating world of programming with our course titled 'Python Basic Programming for Absolute Beginners'. Whether you're a novice looking to embark on a new journey or someone eager to grasp the foundational elements of Python, this course is tailored for you. From setting up Python to crafting your first game and understanding the intricacies of control flow statements, our comprehensive curriculum ensures you grasp every fundamental aspect, setting a robust foundation for your future coding endeavours. Learning Outcomes Understand the core concepts and foundational elements of Python programming. Develop proficiency in working with Python strings, operators, and sequences. Master the art of creating control flow statements and basic Python games. Gain insights into file structures and the application of regular expressions in Python. Successfully complete a Python project, showcasing your newfound knowledge. Why buy this Python Basic Programming for Absolute Beginners? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Python Basic Programming for Absolute Beginners there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this Python Basic Programming for Absolute Beginners for? Beginners with no prior knowledge of programming seeking a structured introduction. Individuals with a curiosity to explore coding as a new skill or hobby. Students desiring to enhance their academic learning with foundational programming knowledge. Professionals from diverse fields looking to broaden their skill set. Educators wishing to acquire beginner-level knowledge for instructional purposes. Prerequisites This Python Basic Programming for Absolute Beginners does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Python Basic Programming for Absolute Beginners 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. Career path Python Developer: Average salary range £45,000 - £70,000. Data Analyst: Average salary range £30,000 - £55,000. 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Game Developer: Average salary range £30,000 - £60,000 Course Curriculum Section 01: Introduction Course Introduction 00:02:00 Course Curriculum 00:04:00 How to get Pre-requisites 00:02:00 Getting Started on Windows, Linux or Mac 00:01:00 Section 02: Introduction To Python And Setting Up Introduction to Python 00:02:00 Python vs Other Languages 00:04:00 Why It's Popular 00:04:00 Command Line Basics 00:07:00 Python Installation (Step By Step) 00:06:00 PyCharm IDE Installation 00:08:00 Getting Start PyCharm IDE 00:05:00 First Python Hello World Program 00:07:00 Assessment Test1 00:01:00 Solution for Assessment Test1 00:01:00 Summary 00:02:00 Section 03: PythonBasic Introduction 00:02:00 Variables 00:16:00 Data Types 00:13:00 Type Casting 00:07:00 User Inputs 00:08:00 Comments 00:04:00 Assessment Test2 00:01:00 Solution for Assessment Test2 00:02:00 Summary 00:02:00 Section 04: Python Strings Introduction 00:02:00 Strings 00:05:00 String Indexing 00:05:00 String Slicing 00:04:00 String Built-in Functions 00:09:00 Formatting String (Dynamic Data) 00:05:00 Assessment Test 00:01:00 Solution for Assessment Test 00:01:00 Summary 00:01:00 Section 05: Python Operators Introduction 00:03:00 Arithmetic Operators 00:08:00 Assignment Operators 00:05:00 Comparison Operators 00:05:00 Logical Operators 00:02:00 AND Operator 00:04:00 OR Operator 00:02:00 NOT Operator 00:03:00 Booleans 00:02:00 Assessment Test4 00:02:00 Solution for Assessment Test4 00:01:00 Summary 00:01:00 Section 06: Python Sequences Introduction 00:02:00 Arrays in Earlier 00:02:00 Lists 00:06:00 Add List Items 00:03:00 Remove List Items 00:01:00 Sort Lists 00:03:00 Join Lists 00:08:00 Tuples 00:08:00 Update tuples 00:07:00 Join tuples 00:02:00 Dictionaries 00:06:00 Add Dictionary Items 00:04:00 Remove Dictionary Items 00:03:00 Nested Dictionaries 00:04:00 Sets 00:04:00 Add Set Items 00:03:00 Remove Set Items 00:01:00 Join Set Items 00:04:00 Assessment Test 00:01:00 Solution for Assessment Test 00:02:00 Summary 00:01:00 Section 07: Python Statements Introduction 00:03:00 If Statement 00:03:00 If-else Statement 00:04:00 If-elif-else Statement 00:04:00 If Statement Coding Exercise 00:05:00 Assessment Test 00:02:00 Solution for Assessment Test 00:02:00 Summary 00:02:00 Section 08: Python Control Flow Statements Introduction 00:04:00 Flow Charts 00:04:00 While Loops Statement 00:10:00 For Loops Statement 00:06:00 Loop through a String 00:03:00 The Break Statement 00:03:00 The Continue Statement 00:02:00 The range() Function 00:04:00 Nested Loops 00:04:00 2D List using Nested Loop 00:04:00 Assessment Test 00:01:00 Solution for Assessment Test 00:03:00 Summary 00:01:00 Section 09: Python Games For Beginners Introduction 00:01:00 Guessing Game 00:07:00 Car Game 00:10:00 Summary 00:01:00 Section 10: Python Functions Introduction 00:02:00 Creating a Function 00:03:00 Calling a Function 00:06:00 Function with Arguments 00:05:00 args, Arbitrary Arguments 00:04:00 kwargs, Arbitrary Keyword Arguments 00:06:00 Summary 00:01:00 Section 11: Working With File Structure Introduction 00:03:00 Reading Files 00:10:00 Creating / Writing Files 00:06:00 Delete Files 00:03:00 Summary 00:01:00 Section 12: Regular Expressions Introduction 00:02:00 RegEx Module 00:07:00 RegEx Functions 00:08:00 Summary 00:02:00 Section 13: PythonProject Introduction 00:02:00 Project Overview 00:03:00 ATM RealTime Project 00:13:00 Summary 00:01:00
Dive deep into the vast realm of Python data science with our meticulously crafted course: 'Python Data Science with Numpy, Pandas and Matplotlib'. Explore the intricate details of Python, setting the stage with Pandas and Numpy, before delving into the power of Python data structures. With topics ranging from Python Strings to Matplotlib Histograms, you'll gain a holistic insight, ensuring that every dataset you touch unveils its story compellingly. So, if you're keen on transmuting raw data into visual masterpieces or insights, this journey is tailor-made for you. Learning Outcomes Grasp foundational knowledge of Python and its data structures like strings, lists, and dictionaries. Understand the potential of NumPy, from basic array operations to handling multi-dimensional arrays. Master the versatility of Pandas, encompassing everything from dataframe conversions to intricate operations like aggregation and binning. Efficiently manage, manipulate, and transform data using Pandas' diverse functionalities. Create visually striking and informative graphs using the power of Matplotlib. Why buy this Python Data Science with Numpy, Pandas and Matplotlib course? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Python Data Science with Numpy, Pandas and Matplotlib there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this Python Data Science with Numpy, Pandas and Matplotlib course for? Beginners eager to jumpstart their journey in Python data science. Analysts looking to enhance their data manipulation skills using Python. Statisticians keen on expanding their toolset with Python-based libraries. Data enthusiasts desiring a deep dive into Python's data libraries and structures. Professionals aiming to upgrade their data visualisation techniques. Prerequisites This Python Data Science with Numpy, Pandas and Matplotlib does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Python Data Science with Numpy, Pandas and Matplotlib 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. Career path Data Scientist: £40,000 - £80,000 Python Developer: £35,000 - £70,000 Data Analyst: £30,000 - £55,000 Business Intelligence Analyst: £32,000 - £60,000 Research Analyst: £28,000 - £52,000 Data Visualization Engineer: £33,000 - £65,000 Course Curriculum Course Introduction and Table of Contents Course Introduction and Table of Contents 00:09:00 Introduction to Python, Pandas and Numpy Introduction to Python, Pandas and Numpy 00:07:00 System and Environment Setup System and Environment Setup 00:08:00 Python Strings Python Strings - Part 1 00:11:00 Python Strings - Part 2 00:09:00 Python Numbers and Operators Python Numbers and Operators - Part 1 00:06:00 Python Numbers and Operators - Part 2 00:07:00 Python Lists Python Lists - Part 1 00:05:00 Python Lists - Part 2 00:06:00 Python Lists - Part 3 00:05:00 Python Lists - Part 4 00:07:00 Python Lists - Part 5 00:07:00 Tuples in Python Tuples in Python 00:06:00 Sets in Python Sets in Python - Part 1 00:05:00 Sets in Python - Part 2 00:04:00 Python Dictionary Python Dictionary - Part 1 00:07:00 Python Dictionary - Part 2 00:07:00 NumPy Library - Introduction NumPy Library Intro - Part 1 00:05:00 NumPy Library Intro - Part 2 00:05:00 NumPy Library Intro - Part 3 00:06:00 NumPy Array Operations and Indexing NumPy Array Operations and Indexing - Part 1 00:04:00 NumPy Array Operations and Indexing - Part 2 00:06:00 NumPy Multi-Dimensional Arrays NumPy Multi-Dimensional Arrays - Part 1 00:07:00 NumPy Multi-Dimensional Arrays - Part 2 00:06:00 NumPy Multi-Dimensional Arrays - Part 3 00:05:00 Introduction to Pandas Series Introduction to Pandas Series 00:08:00 Introduction to Pandas Dataframes Introduction to Pandas Dataframes 00:07:00 Pandas Dataframe conversion and drop Pandas Dataframe conversion and drop - Part 1 00:06:00 Pandas Dataframe conversion and drop - Part 2 00:06:00 Pandas Dataframe conversion and drop - Part 3 00:07:00 Pandas Dataframe summary and selection Pandas Dataframe summary and selection - Part 1 00:06:00 Pandas Dataframe summary and selection - Part 2 00:06:00 Pandas Dataframe summary and selection - Part 3 00:07:00 Pandas Missing Data Management and Sorting Pandas Missing Data Management and Sorting - Part 1 00:07:00 Pandas Missing Data Management and Sorting - Part 2 00:07:00 Pandas Hierarchical-Multi Indexing Pandas Hierarchical-Multi Indexing 00:06:00 Pandas CSV File Read Write Pandas CSV File Read Write - Part 1 00:05:00 Pandas CSV File Read Write - Part 2 00:07:00 Pandas JSON File Read Write Pandas JSON File Read Write Operations 00:07:00 Pandas Concatenation Merging and Joining Pandas Concatenation Merging and Joining - Part 1 00:05:00 Pandas Concatenation Merging and Joining - Part 2 00:04:00 Pandas Concatenation Merging and Joining - Part 3 00:04:00 Pandas Stacking and Pivoting Pandas Stacking and Pivoting - Part 1 00:06:00 Pandas Stacking and Pivoting - Part 2 00:05:00 Pandas Duplicate Data Management Pandas Duplicate Data Management 00:07:00 Pandas Mapping Pandas Mapping 00:04:00 Pandas Grouping Pandas Groupby 00:06:00 Pandas Aggregation Pandas Aggregation 00:09:00 Pandas Binning or Bucketing Pandas Binning or Bucketing 00:08:00 Pandas Re-index and Rename Pandas Re-index and Rename - Part 1 00:04:00 Pandas Re-index and Rename - Part 2 00:05:00 Pandas Replace Values Pandas Replace Values 00:05:00 Pandas Dataframe Metrics Pandas Dataframe Metrics 00:07:00 Pandas Random Permutation Pandas Random Permutation 00:08:00 Pandas Excel sheet Import Pandas Excel sheet Import 00:07:00 Pandas Condition Selection and Lambda Function Pandas Condition Selection and Lambda Function - Part 1 00:05:00 Pandas Condition Selection and Lambda Function - Part 2 00:05:00 Pandas Ranks Min Max Pandas Ranks Min Max 00:06:00 Pandas Cross Tabulation Pandas Cross Tabulation 00:07:00 Matplotlib Graphs and plots Graphs and plots using Matplotlib - Part 1 00:06:00 Graphs and plots using Matplotlib - Part 2 00:02:00 Matplotlib Histograms Matplotlib Histograms 00:03:00 Resource File Resource File - Python Data Science with Numpy, Pandas and Matplotlib 00:00:00
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Discover the power of data science and machine learning with Python! Learn essential techniques, algorithms, and tools to analyze data, build predictive models, and unlock insights. Dive into hands-on projects, from data manipulation to advanced machine learning applications. Elevate your skills and unleash the potential of Python for data-driven decision-making.
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Overview This comprehensive course on Machine Learning with Python will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Machine Learning with Python comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? 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. Who is This course for? There is no experience or previous qualifications required for enrolment on this Machine Learning with Python. It is available to all students, of all academic backgrounds. Requirements Our Machine Learning with Python 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. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 4 sections • 21 lectures • 01:34:00 total length •Introduction to types of ML algorithm: 00:02:00 •SVM - Python Implementation: 00:06:00 •Introduction to types of ML algorithm: 00:02:00 •Importing a dataset in python: 00:02:00 •Resolving Missing Values: 00:06:00 •Managing Category Variables: 00:04:00 •Training and Testing Datasets: 00:07:00 •Normalizing Variables: 00:02:00 •Normalizing Variables - Python Code: 00:03:00 •Summary: 00:01:00 •Simple Linear Regression - How it works?: 00:04:00 •Simple Linear Regreesion - Python Implementation: 00:07:00 •Multiple Linear Regression - How it works?: 00:01:00 •Multiple Linear Regression - Python Implementation: 00:09:00 •Decision Trees - How it works?: 00:05:00 •Random Forest - How it works?: 00:03:00 •Decision Trees and Random Forest - Python Implementation: 00:04:00 •kNN - How it works?: 00:02:00 •kNN - Python Implementation: 00:10:00 •Decision Tree Classifier and Random Forest Classifier in Python: 00:10:00 •SVM - How it works?: 00:04:00
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