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This course offers an immersive experience in data analysis, guiding you from initial setup with Python and Pandas, through series and DataFrame manipulation, to advanced data visualization techniques. Perfect for enhancing your data handling and analysis skills.

Boost Your Career with Apex Learning and Get Noticed By Recruiters in this Hiring Season! Get Hard Copy + PDF Certificates + Transcript + Student ID Card worth £160 as a Gift - Enrol Now With a single payment you will gain access to Newspaper Journalism including 10 additional premium courses, original hard copy certificate, transcript and a student ID card which will allow you to get discounts on things like music, food, travel and clothes etc. Courses are included with this Newspaper Journalism Complete Bundle: * Course 01: Newspaper Journalism * Course 02: Level 2 Microsoft Office Essentials * Course 03: Microsoft Teams * Course 04: Report Writing * Course 05: Working from Home Essentials * Course 06: Mental Health and Working from Home * Course 07: Online Meeting Management * Course 08: Effective Communication Skills * Course 09: Time Management * Course 10: Leadership & Management Diploma * Course 11: Emotional Intelligence and Human Behaviour If you want to gain a solid understanding of Newspaper Journalism and fast track your dream career, then take a step in the right direction with this industry-standard, comprehensive Newspaper Journalism course designed by expert instructors. The Newspaper Journalism will cover a comprehensive range of 13, you'll have 24/7 online access to the study materials, introductory videos, assessment tests, study resources and tutor support for a lifetime. The Newspaper Journalism will help you to develop your skills, confidence and knowledge of this sector, helping to add real value to your CV and personal development. Gain experience online and interact with experts. This can prove to be the perfect way to get noticed by a prospective employer and stand out from the crowd. Newspaper Journalism has been rated and reviewed highly by our learners and professionals alike. We have a passion for teaching, and it shows. All of our courses have interactive online modules that allow studying to take place where and when you want it to. The only thing you need to take Newspaper Journalism is Wi-Fi and a screen. You'll never be late for class again. Experienced tutors and mentors will be there for you whenever you need them, and solve all your queries through email and chat boxes. Whether you are looking to brighten up your CV, just starting out in the industry, looking for a career change or just fancy learning something new, this online Newspaper Journalism course is perfect! Benefits you'll get choosing Apex Learning for this Newspaper Journalism: * One payment, but lifetime access to 11 CPD courses * Certificates, student ID for the title course included in a one-time fee * Full tutor support available from Monday to Friday * Free up your time - don't waste time and money travelling for classes * Accessible, informative modules taught by expert instructors * Learn at your ease - anytime, from anywhere * Study the course from your computer, tablet or mobile device * CPD accredited course - improve the chance of gaining professional skills Curriculum: Module 01: Introduction and Principles * Journalism: An Introduction * Introduction * Forms of Journalism * Influences on Journalism * Principles * Summary Module 02: History and Development * The Print Medium * Newspapers in the Digital Age * Why Newspapers Remain So Powerful * Journalism on the Internet * The UK National Press Today * Common Threads in the History of UK Journalism * Summary Module 03: Interviewing for Newspaper Journalism * Interviewing * The Face-To-Face Interview * The Telephone Interviews * Copy Presentation * Hard News * Softer News * Features * Summary Module 04: News Writing * Introduction to News Writing * Slugs * The Split Page * Punctuation * Rewriting Wire Copy * Conversational Style * Reading Your Copy Aloud * Avoiding Information Overload * News Writing Style * Names and Titles * Numbers, Capital Numbers, Punctuation Marks, and Web Sites * Language * Summary Module 05: News Production * Effective News Gathering Methods * Interviewing * The Deductive and Investigative Methods * Intelligent Deduction * Getting Facts * Sources of Information * Direct Observation * Secondary Sources * Interviews * Press Conferences * Press Notes * Documents * Producing Quality News * Summary Module 06: News Reporting * Reporting the News * Equipment * Reporting Video * Shooting Techniques * Sequences * Reporting Audio * Summary Module 07: Writing Skills for Newspaper Journalists * Getting Down to It * Make A Plan Before You Start * Write Straight onto The Keyboard * Write Notes to Get Started * Revise Your Writing * Master the Basics * Writing News * Writing Reviews * Glossary of Terms Used in Journalism * Summary Module 08: Newspaper Journalism law * Introduction and Background * Types of Law * Divisions of the Law * Defamation * Defamation Act 2013 * Defamation and Human Rights * Reporting Restrictions in Legal Cases * Court Reporting Restrictions * Reporting Restrictions on Cases Involving Children and Young People * Restrictions on Reporting Sexual Offences * Other Main Reporting Restrictions Divorce * Election law * Summary Module 09: Court Reporting * Going to Court * Reporting Court Cases * Contempt of Court * Writing Your Court Report * Summary Module 10: Journalism Ethics * What Are Ethics? * What Makes a Good Journalist? * Morality and Truth * The Right to Respect for Privacy * Freedom of Speech * Copyright * Summary Module 11: Niche Journalism * What Is Niche Journalism? * Importance of Niche Journalism * Introduction to Sports Journalism * Sports Journalism in the 21st Century * Sports Journalism in a Changing Newspaper Market * Broadcasting, Sports Journalism and Entertainment * Television and Sports Journalism * Sports News in The Digital Age * Travel Journalism * Travel Journalism and the Lifestyle * Fashion Journalism * Writing Fashion News and Features * Writing Fashion News * Summary Module 12: Tips on Writing a Good Feature Story * What Is Feature Writing? * The Role of The Feature * Who Is the Feature Writer? * Different Types of Features * Descriptive and Colour Writing * Personality-Celebrity Features * Seasonal Features * Entertainment Features and Critical Writing * Writing Product Reviews for Consumers * Other Forms of Reviews and Criticism * Key Skills of a Feature Writer * How to Get Quotes * Dealing with Quotes * Summary Module 13: Health and Safety for Journalists * Introduction to Health and Safety * Health and Safety at Work * The Main Elements of Health and Safety Law * Reporting in Hostile Environments * Reporting Sports Events * Working As a Freelance * A Summary of Additional Regulations * Summary How will I get my Certificate? After successfully completing the course you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement. * PDF Certificate: Free (Previously it was £10 * 11 = £110) * Hard Copy Certificate: Free (For The Title Course) If you want to get hardcopy certificates for other courses, generally you have to pay £20 for each. But this Fall, Apex Learning is offering a Flat 50% discount on hard copy certificates, and you can get each for just £10! P.S. The delivery inside the U.K. is Free. International students have to pay a £3.99 postal charge. CPD 110 CPD hours / points Accredited by CPD Quality Standards WHO IS THIS COURSE FOR? There is no experience or previous certifications required for enrolment on this course. It is available to all students, of all academic backgrounds. REQUIREMENTS Our Newspaper Journalism is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible on tablets and smartphones so you can access your course on wifi, 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 certifications 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. CERTIFICATES CERTIFICATE OF COMPLETION Digital certificate - Included

Boost Your Career with Apex Learning and Get Noticed By Recruiters in this Hiring Season! Get Hard Copy + PDF Certificates + Transcript + Student ID Card worth £160 as a Gift - Enrol Now With a single payment you will gain access to Data Science Course Bundle 2022 including 10 Career development courses, original hardcopy certificate, transcript and a student ID card which will allow you to get discounts on things like music, food, travel and clothes etc. The world is one big data bank, and data science is one of the most demanding professional sectors of the present era. The analytical and programming-oriented field of data science has limited resources for candidates to learn and develop skills, which is why you need our highly advanced [course_title] course.With step-by-step interactive video content, our training will equip you with extensive knowledge and expertise in data science, including machine learning. This bundle course offers an opportunity to foster your career opportunities with an expert-level understanding of data science and become skilful in this industry. Take this course anywhere and at any time. Don't let your lifestyle limit your learning or your potential. Data Science Course Bundle 2022 will provide you with the CPD certificate that you'll need to succeed. Gain experience online and interact with experts. This can prove to be the perfect way to get noticed by a prospective employer and stand out from the crowd. Data Science Course Bundle 2022 has been rated and reviewed highly by our learners and professionals alike. We have a passion for teaching, and it shows. All of our courses have interactive online modules that allow studying to take place where and when you want it to. The only thing you need to take Data Science Course Bundle 2022 is Wi-Fi and a screen. You'll never be late for class again. Experienced tutors and mentors will be there for you whenever you need them, and solve all your queries through email and chat boxes. Benefits you'll get choosing Apex Learning for this Course: * One payment, but lifetime access to 11 CPD courses * Certificates, student ID for the title course included in a one-time fee * Full tutor support available from Monday to Friday * Free up your time - don't waste time and money travelling for classes * Accessible, informative modules taught by expert instructors * Learn at your ease - anytime, from anywhere * Study the course from your computer, tablet or mobile device * CPD accredited course - improve the chance of gaining professional skills * Gain valuable knowledge without leaving your home What other courses are included with this Course? 1. Level 2 Microsoft Office Essentials 2. Microsoft Teams 3. Leadership & Management Diploma 4. Working from Home Essentials 5. Mental Health and Working from Home 6. Online Meeting Management 7. Effective Communication Skills 8. Time Management 9. Report Writing 10. Emotional Intelligence and Human Behaviour Curriculum ***Data Science Course Bundle 2022*** Welcome, Course Introduction & overview, and Environment set-up * Welcome & Course Overview * Set-up the Environment for the Course (lecture 1) * Set-up the Environment for the Course (lecture 2) * Two other options to setup environment Python Essentials * Python data types Part 1 * Python Data Types Part 2 * Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) * Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) * Python Essentials Exercises Overview * Python Essentials Exercises Solutions Python for Data Analysis using NumPy * What is Numpy? A brief introduction and installation instructions. * NumPy arrays, built-in methods, array methods and attributes. * Indexing, slicing, broadcasting & boolean masking * Arithmetic Operations & Universal Functions * Exercises Overview * Exercises Solutions Python for Data Analysis using Pandas * What is pandas? A brief introduction and installation instructions. * Pandas Introduction * Pandas Data Structures - Series * Pandas Data Structures - DataFrame * Handling Missing Data * Data Wrangling - Combining, merging, joining * Groupby * Useful Methods and Operations * Project 1 (Overview) Customer Purchases Data * Project 1 (Solutions) Customer Purchases Data * Project 2 (Overview) Chicago Payroll Data * Project 2 (Solutions Part 1) Chicago Payroll Data Python for Data Visualization using matplotlib * Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach * Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach * Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach * Matplotlib Essentials - Exercises Overview * Matplotlib Essentials - Exercises Solutions Python for Data Visualization using Seaborn * Introduction & Installation * Distribution Plots * Categorical Plots (Part 1) * Categorical Plots (Part 2) * Axis Grids * Matrix Plots * Regression Plots * Controlling Figure Aesthetics * Exercises Overview * Exercise Solutions Python for Data Visualization using pandas * Pandas Built-in Data Visualization * Pandas Data Visualization Exercises Overview * Panda Data Visualization Exercises Solutions Python for interactive & geographical plotting using Plotly and Cufflinks * Interactive & Geographical Plotting (Part 1) * Interactive & Geographical Plotting (Part 2) * Interactive & Geographical Plotting Exercises (Overview) * Interactive & Geographical Plotting Exercises (Solutions) Capstone Project - Python for Data Analysis & Visualization * Project 1 - Oil vs Banks Stock Price during recession (Overview) * Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) * Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) * Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) * Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) Python for Machine Learning (ML) - scikit-learn - Linear Regression Model * Introduction to ML - What, Why and Types….. * Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff * Linear Regression Model - Hands-on (Part 1) * Linear Regression Model Hands-on (Part 2) * Good to know! How to save and load your trained Machine Learning Model! * Linear Regression Model (Insurance Data Project Overview) * Linear Regression Model (Insurance Data Project Solutions) Python for Machine Learning - scikit-learn - Logistic Regression Model * Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificity…etc. * Logistic Regression Model - Hands-on (Part 1) * Logistic Regression Model - Hands-on (Part 2) * Logistic Regression Model - Hands-on (Part 3) * Logistic Regression Model - Hands-on (Project Overview) * Logistic Regression Model - Hands-on (Project Solutions) Python for Machine Learning - scikit-learn - K Nearest Neighbors * Theory: K Nearest Neighbors, Curse of dimensionality …. * K Nearest Neighbors - Hands-on * K Nearest Neighbors (Project Overview) * K Nearest Neighbors (Project Solutions) Python for Machine Learning - scikit-learn - Decision Tree and Random Forests * Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging…. * Decision Tree and Random Forests - Hands-on (Part 1) * Decision Tree and Random Forests (Project Overview) * Decision Tree and Random Forests (Project Solutions) Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) * Support Vector Machines (SVMs) - (Theory Lecture) * Support Vector Machines - Hands-on (SVMs) * Support Vector Machines (Project 1 Overview) * Support Vector Machines (Project 1 Solutions) * Support Vector Machines (Optional Project 2 - Overview) Python for Machine Learning - scikit-learn - K Means Clustering * Theory: K Means Clustering, Elbow method ….. * K Means Clustering - Hands-on * K Means Clustering (Project Overview) * K Means Clustering (Project Solutions) Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) * Theory: Principal Component Analysis (PCA) * Principal Component Analysis (PCA) - Hands-on * Principal Component Analysis (PCA) - (Project Overview) * Principal Component Analysis (PCA) - (Project Solutions) Recommender Systems with Python - (Additional Topic) * Theory: Recommender Systems their Types and Importance * Python for Recommender Systems - Hands-on (Part 1) * Python for Recommender Systems - - Hands-on (Part 2) Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) * Natural Language Processing (NLP) - (Theory Lecture) * NLP-Challenges, Data Sources, Data Processing ….. * Feature Engineering and Text Preprocessing in Natural Language Processing * NLP - Tokenization, Text Normalization, Vectorization, BoW…. * BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes … * Pipeline feature to assemble several steps for cross-validation… How will I get my Certificate? After successfully completing the course you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement. * PDF Certificate: Free (Previously it was £10 * 11 = £110) * Hard Copy Certificate: Free (For The Title Course) If you want to get hardcopy certificates for other courses, generally you have to pay £20 for each. But this Fall, Apex Learning is offering a Flat 50% discount on hard copy certificates, and you can get each for just £10! P.S. The delivery charge inside the U.K. is £3.99 and the international students have to pay £9.99. CPD 20 CPD hours / points Accredited by CPD Quality Standards WHO IS THIS COURSE FOR? There is no experience or previous qualifications required for enrolment on this Data Science Course Bundle 2022. It is available to all students, of all academic backgrounds. REQUIREMENTS Our Data Science Course Bundle 2022 is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible on tablets and smartphones so you can access your course on wifi, 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 this CPD certificate 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. CERTIFICATES CERTIFICATE OF COMPLETION Digital certificate - Included

> Do you want to formally learn women journalism to be able to achieve this > dream of yours? Then this is the course you will need right now. DESCRIPTION: Journalism is the activity that involves writing for newspapers, magazines, and another broadcasting medium. Journalism is a form of communication and information dissemination media. In this course, we will discuss the imperfections of journalism and how to cope with this dilemma and the road towards journalism. You will be learning about being the perfect journalist aspirant and know the style that will suit you. Moreover, you will be learning about outside contributors and the search for a copy. This course will be providing the basics and the core skills needed for working and aspiring journalists. This course will also guide you through the core pillars of an effective news story. You will also learn the deep significance of journalism and how this can affect the career of a journalist. Lastly, this course will be discussing the importance of journalism to the society and its impact. WHO IS THE COURSE FOR? * Professionals, businessmen, and entrepreneurs who are in the journalism sector. * People who have an interest in writing and journalism. ENTRY REQUIREMENT: * This course is available to all learners, of all academic backgrounds. * Learners should be aged 16 or over to undertake the qualification. * Good understanding of English language, numeracy and ICT are required to attend this course. ASSESSMENT:  * At the end of the course, you will be required to sit an online multiple-choice test. Your test will be assessed automatically and immediately so that you will instantly know whether you have been successful. * Before sitting for your final exam you will have the opportunity to test your proficiency with a mock exam. CERTIFICATION: * After you have successfully passed the test, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. * PDF certificate's turnaround time is 24 hours and for the hard copy certificate, it is 3-9 working days. WHY CHOOSE US? * Affordable, engaging & high-quality e-learning study materials; * Tutorial videos/materials from the industry leading experts; * Study in a user-friendly, advanced online learning platform; * Efficient exam systems for the assessment and instant result; * The UK & internationally recognised accredited qualification; * Access to course content on mobile, tablet or desktop from anywhere anytime; * The benefit of career advancement opportunities; * 24/7 student support via email. CAREER PATH: Level 2 Certificate in Women Journalism is a useful qualification to possess and would be beneficial for the following careers: * Anchors * Bloggers * Broadcasters * Entrepreneurs * Freelancers * Journalist * News Writer * Online Writers * Social Media Specialist * Social Content Creator * Virtual Assistants. Newspaper Journalism What is news? 01:00:00 What is a journalist? 01:00:00 The shape of the news story 00:15:00 Writing the intro in simple steps 01:00:00 Writing the intro, the golden rules 00:30:00 Writing the news story in simple steps 01:00:00 Writing the news story - clear writing 00:30:00 Quotes 01:00:00 Attribution 00:30:00 TV Journalism News Gathering 00:30:00 Enterprising Stories 00:30:00 Watch your interviewee's body language. 00:15:00 Working with Sources 00:15:00 Covering Events 01:00:00 Computer-Assisted Reporting 00:30:00 Glossary of Broadcast News Teams 00:15:00 Law, Ethics And Responsibility 00:15:00 Operating Standards for News and Public Affairs 00:15:00 Lighting 00:15:00 Media What is the Media? 00:15:00 What Makes News? 00:30:00 Plan your Approach 01:00:00 Adhere to Deadlines 00:30:00 The Interview 00:15:00 Social Media and Journalism Definition of Social Media 00:15:00 Communication flow within journalism 00:15:00 The impact of social media on journalism 00:30:00 Women in Journalism The Secret Significance of Journalism 01:00:00 Imperfections of the Existing Woman−Journalist 01:00:00 The Roads towards Journalism 01:00:00 The Aspirant 01:00:00 Style 01:00:00 The Outside Contributor 01:00:00 The Search for Copy 01:00:00 The Art of Corresponding with an Editor 00:30:00 Notes on the Leading Types of Papers 00:30:00 Woman's Sphere in Journalism 01:00:00 Conclusion 00:15:00 Mock Exam Mock Exam- Level 2 Certificate in Women Journalism 00:30:00 Final Exam Final Exam- Level 2 Certificate in Women Journalism 00:30:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

This course first equips you with the fundamentals of Python and then progresses to teach you how to use various libraries such as NumPy, Pandas, Seaborn, Bokeh, and so on. This course contains several mini projects so that, by the end of this course, you will be equipped with the essential tools you need to become a visualization expert.

OVERVIEW This comprehensive course on Python Programming: Beginner To Expert will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Python Programming: Beginner To Expert comes with accredited certification from CPD, 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 Python Programming: Beginner To Expert. It is available to all students, of all academic backgrounds. REQUIREMENTS Our Python Programming: Beginner To Expert 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 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- * Open doors of opportunities * Increase your adaptability * Keep you relevant * Boost confidence And much more! COURSE CURRICULUM 18 sections • 121 lectures • 15:27:00 total length •Intro To Python Section Overview: 00:05:00 •What is Python Programming: 00:10:00 •Who is This Course For: 00:05:00 •Python Programming Marketplace: 00:06:00 •Python Job Opportunities: 00:05:00 •How To Land a Python Job Without a Degree: 00:08:00 •Python Programmer Job Roles: 00:09:00 •Python from A-Z Course Structure: 00:04:00 •Getting Familiar with Python Section Overview: 00:06:00 •Installing Python on Windows: 00:10:00 •Anaconda and Jupyter Notebooks Part 1: 00:08:00 •Anaconda and Jupyter Notebooks Part 2: 00:16:00 •Comments: 00:05:00 •Python Syntax: 00:02:00 •Line Structure: 00:03:00 •Line Structure Exercise: 00:07:00 •Joining Lines: 00:05:00 •Multiple Statements on a Single Line: 00:05:00 •Indentation: 00:08:00 •Basic Data Types Section Overview: 00:08:00 •String Overview: 00:10:00 •String Manipulation: 00:07:00 •String Indexing: 00:04:00 •String Slicing: 00:08:00 •Printing: 00:10:00 •Python Variables: 00:08:00 •Integers and Floats: 00:08:00 •Booleans: 00:05:00 •Mini Project 1 : Letter Counter: 00:20:00 •Python Operators Section Overview: 00:04:00 •Comparison Operators: 00:09:00 •Arithmetic Operators: 00:08:00 •Assignment Operators: 00:04:00 •Logical Operators: 00:13:00 •Identity Operators: 00:05:00 •Membership Operators: 00:02:00 •Bitwise Operators: 00:08:00 •Python Advanced Data Types Section Overview: 00:11:00 •Sets: 00:06:00 •List Overview: 00:05:00 •List Slicing and Indexing: 00:04:00 •Tuples: 00:02:00 •When to use each one?: 00:05:00 •Compound Data Types: 00:03:00 •Dictionaries: 00:11:00 •Control Flow Part 1 Section Overview: 00:15:00 •Intro to Control Flow: 00:01:00 •Basic Conditional Statements: 00:14:00 •More Conditional Statements: 00:05:00 •For Loops: 00:10:00 •While Loops: 00:12:00 •Control Flow Part 2 Section Overview: 00:02:00 •Break Statements: 00:08:00 •Continue Statements: 00:05:00 •Zip Function: 00:07:00 •Enumerate Function: 00:04:00 •List Comprehension: 00:04:00 •Python Functions Section Overview: 00:03:00 •Intro to Functions: 00:02:00 •Python help Function: 00:03:00 •Defining Functions: 00:09:00 •Variable Scope: 00:08:00 •Doc Strings: 00:04:00 •User Input and Error Handling Section Overview: 00:02:00 •Introduction to error handling: 00:03:00 •User Input: 00:04:00 •Syntax Errors: 00:04:00 •Exceptions: 00:11:00 •Handling Exceptions Part 1: 00:08:00 •Handling Exceptions Part 2: 00:08:00 •Python Advanced Functions Section Overview: 00:05:00 •Lambda Functions: 00:05:00 •Functions args and kwargs: 00:10:00 •Iterators: 00:08:00 •Generators and Yield: 00:12:00 •Map Function: 00:14:00 •Filter Function: 00:08:00 •Python Scripting and Libraries Section Overview: 00:05:00 •What is a script: 00:01:00 •What is an IDE: 00:17:00 •What is a text editor?: 00:12:00 •From Jupyter Notebook to VScode Part 1: 00:15:00 •From Jupyter Notebook to VScode Part 2: 00:05:00 •Importing Scripts: 00:03:00 •Standard Libraries: 00:04:00 •Third Party Libraries: 00:06:00 •NumPy Section Overview: 00:04:00 •Intro to NumPy: 00:04:00 •Why use NumPy?: 00:04:00 •NumPy Arrays: 00:10:00 •Reshaping, Accessing, and Modifying: 00:07:00 •Slicing and Copying: 00:06:00 •Inserting, Appending, and Deleting: 00:10:00 •Array Logical Indexing: 00:04:00 •Broadcasting: 00:08:00 •Intro to Pandas: 00:17:00 •Pandas Series: 00:17:00 •Pandas Series Manipulation: 00:17:00 •Pandas DataFrame: 00:17:00 •Pandas DataFrame Manipulation: 00:13:00 •Dealing with Missing Values: 00:10:00 •Functional vs OOP: 00:06:00 •OOP Key Definitions: 00:04:00 •Create your First Class: 00:12:00 •How to Create and Use Objects: 00:06:00 •How to Modify Attributes: 00:12:00 •Python Decorators: 00:27:00 •Property Decorator: 00:09:00 •Class Method Decorator: 00:07:00 •Static Methods: 00:10:00 •Inheritance from A to Z: 00:21:00 •Python Career Section Overview: 00:06:00 •Getting Started with Freelancing: 00:09:00 •Building A Brand: 00:12:00 •Personal Branding: 00:13:00 •Importance of Having Website/Blog: 00:04:00 •Do's And Don'ts Of Networking: 00:06:00 •Top Freelance Websites: 00:08:00 •Creating A Python Developer Resume: 00:06:00 •Resources - Python Programming: Beginner To Expert: 00:00:00 •Assignment - Python Programming: Beginner To Expert: 00:00:00

OVERVIEW This comprehensive course on Python for Data Analysis will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Python for Data Analysis 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 Python for Data Analysis. It is available to all students, of all academic backgrounds. REQUIREMENTS Our Python for Data Analysis 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 19 sections • 99 lectures • 00:08:00 total length •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 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 •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 •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 •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 •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 •Pandas Built-in Data Visualization: 00:34:00 •Pandas Data Visualization Exercises Overview: 00:03:00 •Panda Data Visualization Exercises Solutions: 00:13:00 •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 •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 •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 •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 •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 •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 •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 •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 •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 •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 •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- Python for Data Analysis: 00:00:00

COURSE OVERVIEW Julia is one of the highest performing programming languages. The Tutorials - The Julia Programming Language course is designed to train you in this valuable programing language. In this course, you will get equipped with the skills to code in Julia and add available skill sets to your resume. The Tutorials - The Julia Programming Language course will introduce you to the basic principles of Julia programming language. In this course, you will learn the steps to install Julia. You will get introduced to Julia variables, integers, sign function and more. The course will provide you with lectures based on Cher types and strings. You will start to understand all the functions of this programming language. The course will give you an extensive understanding of Julia Dict and type. By the end of the course, you will pick up all the valuable information and skills to use this language. Learn the ins and outs of Julia programming language from the Tutorials - The Julia Programming Language course. This course will increase your abilities and boost your employability in the relevant industry. LEARNING OUTCOMES * Understand the process of installing Julia * Familiarize yourself with Julia variables and functions * Enrich your understanding of Cher types and strings * Learn the details of conditional and non-conditional blocks * Grasp the skills essential for Juila Dict operations WHO IS THIS COURSE FOR? This Tutorials - The Julia Programming Language course is suitable for programmers, data scientists, or individuals who want to learn a new programming language. ENTRY REQUIREMENT * This course is available to all learners, of all academic backgrounds. * Learners should be aged 16 or over to undertake the qualification. * Good understanding of English language, numeracy and ICT are required to attend this course. CERTIFICATION * After you have successfully completed the course, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy at the cost of £39 or in PDF format at the cost of £24. * PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days. WHY CHOOSE US? * Affordable, engaging & high-quality e-learning study materials; * Tutorial videos/materials from the industry-leading experts; * Study in a user-friendly, advanced online learning platform; * Efficient exam systems for the assessment and instant result; * The UK & internationally recognized accredited qualification; * Access to course content on mobile, tablet or desktop from anywhere anytime; * The benefit of career advancement opportunities; * 24/7 student support via email. CAREER PATH The Tutorials - The Julia Programming Language course is a useful qualification to possess and would be beneficial for any related profession or industry such as: * Programmer  * Data Scientist  Introduction Learning Julia 00:01:00 Installing Julia 00:06:00 Installing Juno 00:04:00 Begin Dancing with Julia Julia Variables 00:05:00 Julia Integers and Floats 00:05:00 Julia Convert and Comparisons 00:03:00 Rounding Operations 00:05:00 Division Function 00:04:00 Sign Function and Power 00:05:00 Complex and Rational Numbers 00:05:00 Julia Chars and Strings Julia Char type 00:03:00 String Literals 00:02:00 Extract Char and String 00:02:00 Concatenate and Interpolate 00:03:00 isEqual and Comparisons 00:04:00 Find and OccursIn 00:05:00 Repeat and Regex 00:04:00 Julia Functions Julia Function Object 00:04:00 Function Return Type 00:06:00 Functions as Objects and Arguments 00:04:00 Operators as Functions 00:02:00 Anonymous Function 00:04:00 Function Arguments Tuples 00:05:00 Unpacking Tuples 00:02:00 Varargs 00:03:00 Optional Arguments 00:03:00 Keyword Arguments 00:03:00 Conditional and Non-Conditional Blocks Do Block 00:04:00 Compound Expression 00:02:00 If Statements 00:05:00 If Statement Return Value 00:02:00 Short Circuit Evaluation 00:03:00 Loops and Exceptions For Loop 00:02:00 Control and Nest For Loops 00:03:00 Exceptions 00:03:00 Julia Try and Catch 00:03:00 While Loop 00:02:00 Variable Scope 00:05:00 Arrays in Julia Arrays 00:04:00 Pop and Push 00:03:00 Multidimensional Arrays 00:03:00 Copying Arrays 00:02:00 Julia Dicts Dicts 00:02:00 Dict Operations 00:02:00 More Dict Operations 00:04:00 More Cool Dict Operations 00:03:00 One More Cool Dict Operation 00:04:00 Broadcasting 00:04:00 Julia Types Julia Types 00:01:00 Verify and Specify Types 00:03:00 More Verification and Specification 00:05:00 Julia Methods 00:02:00 Composite Types 00:05:00 Mutable Structs 00:02:00 Constructor Functions 00:04:00 Modules and Packages Julia Modules 00:02:00 Using Packages 00:04:00 User Defined Modules 00:05:00 Working with Text Files Reading Text Files 00:04:00 Writing To Text Files 00:03:00 Writing Collections To Files 00:02:00 Julia Date and Time Date And Time 00:03:00 Date Queries 00:02:00 Date Arithmetic 00:03:00 Meta Programming in Julia Meta Programming 00:02:00 Quoted Expression 00:04:00 Macros 00:02:00 REST APIs and MySQL Using Genie 00:04:00 Payloads and POST Requests 00:05:00 Julia and MySQL 00:08:00 DataFrames and Plots DataFrames 00:05:00 Plotting with Plots 00:02:00 Where to go from here 00:01:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

OVERVIEW In this age of technology, data science and machine learning skills have become highly demanding skill sets. In the UK a skilled data scientist can earn around £62,000 per year. If you are aspiring for a career in the IT industry, secure these skills before you start your journey. The Complete Machine Learning & Data Science Bootcamp 2023 course can help you out. This course will introduce you to the essentials of Python. From the highly informative modules, you will learn about NumPy, Pandas and matplotlib. The course will help you grasp the skills required for using python for data analysis and visualisation. After that, you will receive step-by-step guidance on Python for machine learning. The course will then focus on the concepts of Natural Language Processing.  Upon successful completion of the course, you will receive a certificate of achievement. This certificate will help you elevate your resume. So enrol today! 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? Anyone with an interest in learning about data science can enrol in this course. It will help aspiring professionals develop the basic skills to build a promising career. Professionals already working in this can take the course to improve their skill sets. REQUIREMENTS 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.   CAREER PATH 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 * Data Analyst  * Data Scientist  * Data Manager  * Business Analyst COURSE CURRICULUM 18 sections • 98 lectures • 23:48:00 total length •Welcome & Course Overview6: 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 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 •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 •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 •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 •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 •Pandas Built-in Data Visualization: 00:34:00 •Pandas Data Visualization Exercises Overview: 00:03:00 •Panda Data Visualization Exercises Solutions: 00:13:00 •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): 00:17:00 •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 •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 •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 •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 •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 •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 •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 •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 •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 •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

This course will show you why Hadoop is one of the best tools to work with big data. With the help of some real-world data sets, you will learn how to use Hadoop and its distributed technologies, such as Spark, Flink, Pig, and Flume, to store, analyze, and scale big data.