Learn Data Science

Ask clear questions, analyze data, and explain what the evidence supports.

Start learning 5 lessons · about 1 hours · free
About this track

Learn a practical data science workflow: frame a question, inspect and clean data, summarize patterns, choose useful visualizations, and communicate conclusions with care. Exercises use Python and run in the browser.

Before you start
  • No prior data science experience is needed.
  • Basic familiarity with Python is helpful but not required.
  • Exercises use Python; they do not require external packages.
  1. Unit 1 · 0/2 lessons

    Data foundations

    Frame a question and inspect the data. Badge: Data explorer

    1. 0x001Start with a data questionTurn a broad curiosity into a question that data can help answer. 12 min 0/1 exercises solved 12 min 0/1 exercises solved
    2. 0x102Inspect and clean a datasetCheck values, missing entries, and types before calculating. 12 min 0/1 exercises solved 12 min 0/1 exercises solved
  2. Unit 2 · 0/3 lessons

    Analysis and communication

    Summarize, visualize, and evaluate evidence. Badge: Evidence reader

    1. 0x203Summarize and compare groupsUse descriptive statistics to describe distributions and group differences. 12 min 0/1 exercises solved 12 min 0/1 exercises solved
    2. 0x304Choose a useful visualizationMatch charts to comparisons, distributions, and relationships. 12 min 0/1 exercises solved 12 min 0/1 exercises solved
    3. 0x405Evaluate evidence and communicate limitsCheck whether a conclusion is supported and explain uncertainty clearly. 12 min 0/1 exercises solved 12 min 0/1 exercises solved
Did you like the lesson? 😆👍
Consider a donation to support our work:
See donation links