Tech World Software SchoolTWSS

from first concept to confident practice

Data Science

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

Start learning 10 lessons · first lesson about 18 min · free · no account needed
About this track

Learn the full data science workflow with Python and pandas: frame a question, load and clean messy data, summarize and visualize it, measure relationships and uncertainty, run A/B tests, and report what the evidence does - and doesn’t - support.

Along the way you’ll drag outliers around a distribution, discover that identical statistics can hide completely different data, fit regression lines by hand, watch the central limit theorem build up sample by sample, and catch Simpson’s paradox in the act. Everything runs in your browser - including pandas, which downloads automatically the first time a program uses it.

Before you start
  • No prior data science experience is needed.
  • Basic Python helps; pandas is introduced from scratch.
  • A modern browser with JavaScript enabled.

Your path

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  1. Unit 1 · 0/3 lessons

    Data foundations

    Frame a question, load data with pandas, make it tidy, and clean it. Badge: Data explorer

    1. 0x001Start with a data questionTurn a broad curiosity into a question data can answer, and learn the workflow and vocabulary of data science. 18 min 0/2 exercises solved 18 min 0/2 exercises solved
    2. 0x102Load data and make it tidyRead CSV files with pandas, inspect their shape, and reshape messy tables into tidy ones. 22 min 0/2 exercises solved 22 min 0/2 exercises solved
    3. 0x203Inspect and clean a datasetFind missing values, duplicates, inconsistent labels, wrong units and outliers - and handle each deliberately. 24 min 0/3 exercises solved 24 min 0/3 exercises solved
  2. Unit 2 · 0/3 lessons

    Explore and summarize

    Summarize distributions and groups, choose honest charts, and measure relationships. Badge: Pattern finder

    1. 0x304Summarize and compare groupsDescribe the center and spread of a distribution, and compare groups with groupby. 22 min 0/3 exercises solved 22 min 0/3 exercises solved
    2. 0x405Choose a useful visualizationMatch charts to questions, see why summaries alone can mislead, and avoid charts that distort. 22 min 0/2 exercises solved 22 min 0/2 exercises solved
    3. 0x506Relationships: correlation and regressionMeasure how two variables move together, fit a line by least squares, and know what neither can tell you. 24 min 0/2 exercises solved 24 min 0/2 exercises solved
  3. Unit 3 · 0/3 lessons

    Evidence and uncertainty

    Quantify uncertainty, run A/B tests, and judge and communicate evidence. Badge: Evidence reader

    1. 0x607Samples, uncertainty and confidence intervalsSee how estimates vary from sample to sample, and put honest error bars on them. 24 min 0/2 exercises solved 24 min 0/2 exercises solved
    2. 0x708A/B tests and p-valuesRun a fair experiment, measure the lift, and judge whether a difference could be chance - without misreading p-values. 24 min 0/2 exercises solved 24 min 0/2 exercises solved
    3. 0x809Evaluate evidence and communicate limitsSpot selection bias, confounding and Simpson’s paradox, and report findings in proportion to the evidence. 22 min 0/2 exercises solved 22 min 0/2 exercises solved
  4. Unit 4 · 0/1 lessons

    Capstone

    Clean and analyze a bike-share dataset and report the findings. Badge: Data scientist

    1. 0x9010Capstone: analyze a bike-share datasetTake a messy export from raw rows to a short, honest report. 35 min 0/2 exercises solved 35 min 0/2 exercises solved