Data Science Fundamentals
Build a complete data science foundation — from Python programming and pandas to data wrangling, visualization, statistical thinking, machine learning, and communicating results. Designed for aspiring data scientists and analysts.
14 chapters across 3 books
What Is Data Science?
Intro to Data Science
Python Fundamentals I
Intro to Data Science
Introduction to pandas
Intro to Data Science
Cleaning Messy Data
Intro to Data Science
Grammar of Graphics
Intro to Data Science
Descriptive Statistics
Intro to Data Science
Linear Regression
Intro to Data Science
Decision Trees & Random Forests
Intro to Data Science
Evaluating Models
Intro to Data Science
Communicating Results
Intro to Data Science
Introduction to pandas
Python for Business
Descriptive Statistics
Python for Business
Designing Studies
Intro Statistics
Communicating with Data
Intro Statistics
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Machine Learning 18 chapters Python for Data Science 8 chapters Neural Networks & Deep Learning 9 chapters Probability & Statistics 15 chapters Sports Betting Analytics 16 chapters Natural Language Processing (NLP) 12 chapters Data Visualization 9 chapters Sports Analytics 14 chapters Predictive Modeling & Forecasting 17 chapters Computer Vision 8 chapters AI-Assisted Software Development 12 chapters AI Agents & Autonomous Systems 6 chapters Software Engineering Best Practices 11 chapters AI Ethics & Governance 18 chapters Cybersecurity & Ethical Hacking 17 chapters Applied Psychology 16 chapters Python for Business 15 chapters Working with AI Tools 12 chapters Creator Economy & Digital Entrepreneurship 11 chapters Data Governance & Privacy 12 chapters Conflict Resolution & Communication 9 chapters Fan Studies & Internet Culture 11 chapters Luck, Probability & Decision-Making 10 chapters Home Systems & Maintenance 9 chapters Regulatory Technology & Compliance 10 chapters AI & Machine Learning for Business 10 chapters COBOL Programming 10 chapters Political Analytics & Data 10 chapters Propaganda & Disinformation 9 chapters Psychology of Attraction & Relationships 9 chapters AI Literacy & Education 13 chapters Computer Science Fundamentals 10 chapters Surveillance, Privacy & Digital Rights 12 chapters Algorithms & Their Impact on Society 8 chapters Learning Science & Metacognition 20 chapters Systems Thinking & Mental Models 20 chapters Mainframe & COBOL Programming 14 chapters Database Systems 13 chapters Statistics & Probability 14 chapters Cognitive Science & Critical Thinking 13 chapters Learning Science & Study Skills 14 chapters Quantum Physics & Wave Mechanics 12 chapters Appalachian Studies 12 chapters Epistemic Failure & How Knowledge Goes Wrong 13 chapters