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Data · Beginner → Expert

📊 Statistics and Data Science

Master descriptive and inferential statistics, probability, experimentation, modeling, feature engineering, evaluation, communication and reproducible analysis.

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Course roadmap

Pass each module exam to unlock the next module.

Module 1 · Beginner

Data Science Workflow and Reproducible Analysis

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Module 2 · Beginner

Descriptive Statistics and Data Distributions

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Module 3 · Beginner

Probability Foundations and Random Variables

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Module 4 · Beginner

Sampling, Bias and Estimation

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Module 5 · Intermediate

Confidence Intervals and Hypothesis Testing

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Module 6 · Intermediate

Correlation, Causation and Confounding

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Module 7 · Intermediate

Experimental Design and A/B Testing

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Module 8 · Intermediate

Linear Regression and Diagnostics

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Module 9 · Advanced

Classification and Logistic Regression

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Module 10 · Advanced

Feature Engineering and Preprocessing

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Module 11 · Advanced

Model Validation, Cross-Validation and Leakage

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Module 12 · Advanced

Tree Models and Ensemble Methods

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Module 13 · Advanced

Unsupervised Learning and Clustering

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Module 14 · Expert

Time Series Analysis Fundamentals

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Module 15 · Expert

Communicating Uncertainty and Decision Impact

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Module 16 · Expert

Ethics, Privacy and Responsible Data Practice

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Module 17 · Expert

Expert Capstone: Evidence-Driven Data Science Project

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Certification gate

Final course exam

Pass mark: 80%. Time limit: 360 minutes. All module exams must be passed first.

Locked until modules are passed