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Data Science
Use statistics, programming, and reproducible workflows to answer questions with data.
TechnologyUniversityIllustrative 4 years path
Curriculum outline
Year 1 · Working with data
Programming, data visualization, descriptive statistics, calculus, and linear algebra.
Year 2 · Inference and data systems
Probability, statistical inference, data structures, SQL, and reproducible workflows.
Year 3 · Models and evaluation
Regression, machine learning, experimental design, model validation, and data ethics.
Year 4 · Applied data project
Apply these methods in a domain such as health, economics, or the environment. Publish a reproducible analysis with limitations.
Curriculum reference · UC Berkeley
This roadmap is designed for university-level self-study.
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Virtual labs and practical activities
Free practical activities will be added as lessons are published on this path.