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Free course
Data Science Tutorial
Learn data science from raw data to real business decisions, step by step, in simple words. Every idea is shown with animations, real Python and SQL, and a real coffee chain dataset.
What you will learn
- Pandas, cleaning data and exploring it properly
- Statistics: sampling, confidence and p-values
- A/B testing, power, peeking, Bayesian tests and bandits
- SQL, window functions and DuckDB
- Cause and effect: regression and natural experiments
- Forecasting, simulation and decisions under uncertainty
- Charts, storytelling and dashboards
- Six case studies, a capstone and interview preparation
Course contents
Every lesson has its own page with the explanation, code you can copy, the real output, screenshots from the video, and a link that jumps straight to that moment in the video.
1. What Data Science Is
2. Pandas in Depth
- Pandas Essentials7:54
- Grouping and Aggregating9:20
- Dates and Trends10:46
- Joining Tables12:11
3. Cleaning and Exploring
- Messy Real Data13:43
- Repeatable Cleaning15:21
- Seeing Distributions16:42
- Relationships17:43
4. Statistics: Signal or Luck
5. Experiments
- A/B Testing26:11
- How Much Data Do You Need?27:41
- More Statistical Tests29:48
6. SQL and Customers
- SQL Essentials31:38
- Window Functions33:14
- Customer Analytics35:18
7. Cause and Effect
8. Forecasting and Charts
- Forecasting Sales42:15
- Charts That Persuade44:56
9. Storytelling and Tools
10. Advanced Data Wrangling
- Reshaping Tables51:16
- Text Columns53:39
- Big Files55:11
11. Time and Journeys
- Rolling Windows58:03
- Catching Anomalies59:34
- Funnels1:01:09
- Retention Curves1:02:45
12. Products and Prices
- What Sells Together1:04:16
- Pricing and Discounts1:05:56
- Bayesian A/B Testing1:07:39
- Cutting Test Noise1:09:19
13. Advanced Causal Thinking
- Learning While Earning1:10:38
- Fair Comparisons1:12:08
- Regression Discontinuity1:13:43
- Uplift Modelling1:15:13
14. Forecasting in Practice
- Backtesting Forecasts1:16:53
- Forecasting Many Series1:18:31
- From Forecast to Decision1:19:54
15. Randomness in Business
- Modelling Arrivals1:21:21
- How Many Baristas?1:23:27
- How Long Do Customers Stay?1:25:31
16. Deciding Under Uncertainty
- Monte Carlo Simulation1:27:22
- What Matters Most?1:29:14
- Payback Time1:30:18
17. Trustworthy Measurement
- Fixing a Biased Survey1:31:47
- Broken Experiments1:33:22
- Testing Your Tests1:34:31
18. Hidden Selection
- Selection Bias1:36:10
- Survivorship Bias1:37:41
- Instrumental Variables1:38:49
19. Before and After
- Synthetic Control1:40:27
- Interrupted Time Series1:41:59
- Handling Outliers1:43:06
20. Modern Analyst Tools
- Why Data Goes Missing1:44:39
- Reducing Columns1:46:17
- Your AI Analyst1:47:23
21. More Sharp Tools
- The Bootstrap1:49:46
- Testing Many Things at Once1:52:30
- Customer Segments1:55:00
- The 80/20 Rule1:57:35
22. Reliable Analysis
- Data Checks2:00:06
- Automated Reports2:01:33
- Reproducible Analysis2:02:52
23. Metrics and Responsibility
- Choosing Metrics2:04:44
- Privacy2:06:42
- Fairness2:08:21
- Working with Stakeholders2:09:55
24. Better Charts and Your Career
- Interactive Charts2:11:42
- Small Multiples2:13:00
- Heatmaps2:13:59
- Harder SQL Questions2:14:59
- Product Case Questions2:16:23
- Your Portfolio2:17:41
25. Case Study: The Summer Panic
- Case Study: The Summer Panic2:18:56
26. Case Study: Staffing
27. Case Study: The Redesign
28. Case Studies: Menu and Customers
- Case Study: Simplifying the Menu2:28:46
- Case Study: Who to Keep2:31:14
- Case Study: The Annual Review2:33:38
29. Review: Core Skills
- Review: Data Skills2:35:36
- Review: Experiments2:39:00
- Review: Causes and Decisions2:42:33
30. Myths and Hard Questions
- Data Science Myths2:46:17
- Explaining Hard Ideas2:48:17
- Hard Interview Questions2:50:16
31. Capstone: The Big Question
- Capstone: The Big Question2:52:09
- Capstone: The Recommendation2:54:20
32. Quizzes and Careers
- Quiz: Foundations2:56:16
- Quiz: Statistics3:01:37
- Interview Questions3:07:03
- Your Cheat Sheet3:08:39
- Your Roadmap3:09:32