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Learning path

Data Scientist

Python, R, and SQL — the canonical trio of data analysis. Plus the data structures that underlie efficient queries (bloom filters, tries, search engines).

mixed12 courses113 lessons~28 hoursFree
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Course sequence

  1. 01

    Python Fundamentals

    Not started

    Start from zero and build a solid Python foundation. You will learn variables, data types, conditionals, loops, and string manipulation through hands-on exercises with real code execution.

    beginnerpython13 lessons~3h
  2. 02

    Python in Practice

    Not started

    Go beyond the basics. Master lists, dictionaries, functions, and file handling through practical exercises that mirror real-world programming tasks.

    intermediatepython12 lessons~3h
  3. 03

    Advanced Python

    Not started

    Level up with object-oriented programming, generators, decorators, and real-world patterns. This course is for programmers who know the fundamentals and want to write professional Python.

    advancedpython9 lessons~2h
  4. 04

    R Fundamentals

    Not started

    Learn R: the lingua franca of statistics and data science. Vectors are everything. Built for analysts, used by epidemiologists, economists, and biologists. Tidy syntax once you grok the vector mindset.

    beginnerr9 lessons~2h
  5. 05

    R Intermediate

    Not started

    Level up from R Fundamentals. Apply family in depth, S3 classes, regex, factor types, basic statistics. The features data scientists reach for daily.

    intermediater7 lessons~2h
  6. 06

    R Advanced

    Not started

    Beyond R Intermediate. Environments, lexical scoping, S4 classes, vectorization tricks, NSE basics, profvis. The features behind tidyverse and serious R packages.

    advancedr7 lessons~2h
  7. 07

    SQL Fundamentals

    Not started

    Learn SQL: the language for talking to databases. Used by literally every backend that stores anything. SELECT, JOIN, GROUP BY, aggregates, subqueries — once you have these you can answer any question your data can answer.

    beginnersql10 lessons~3h
  8. 08

    SQL Intermediate

    Not started

    Level up from SQL Fundamentals. Subqueries, CTEs, window functions, set operations, transactions, indexes. The SQL features serious analytics and reporting use every day.

    intermediatesql7 lessons~2h
  9. 09

    SQL Advanced

    Not started

    Beyond SQL Intermediate. Indexes, query optimization mental model, complex joins, JSON, advanced window functions, recursive CTEs. The features behind serious analytics and reporting.

    advancedsql7 lessons~2h
  10. 10

    Build a Bloom Filter

    Not started

    Build the probabilistic set data structure used in databases (LevelDB, BigTable), web crawlers, Bitcoin SPV, and CDN cache invalidation. Implement basic, counting, and scalable variants. Master the math: bits per item, hash count, false positive rate.

    beginner11 lessons~3h
  11. 11

    Build a Trie / Autocomplete

    Not started

    Build a trie (prefix tree) with insert, search, prefix queries, deletion, radix compression, top-K autocomplete, and fuzzy search. Used in IDE autocomplete, browser address bars, IP routing, and spell checkers.

    beginner8 lessons~2h
  12. 12

    Build Your Own Search Engine

    Not started

    Build a full-text search engine from scratch. You'll tokenize documents, build inverted indexes with positions, support boolean and phrase queries, rank with TF-IDF and BM25, add field boosts, compress posting lists with VByte+delta encoding, and even add spell correction. By the end you'll deeply understand how Lucene, Elasticsearch, Tantivy, and Meilisearch actually work.

    intermediate13 lessons~3h

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Data Scientist