Data Science & Analytics with Python · Tutorial tracks

Python for data science

NumPy-first mental models, tidy pandas workflows, visualization discipline.

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Lesson outline

  1. 61
    Python for data science — Part 033

    Placeholder slot — edit in console (python-data-science-stub-033).

  2. 62
    Read JSON and API Data into pandas

    Read JSON and API data into pandas — Python for data science.

  3. 63
    Python for data science — Part 034

    Placeholder slot — edit in console (python-data-science-stub-034).

  4. 64
    Combine Datasets with Concat and Append

    Learn to combine datasets using pandas concat and append in Python for data science. Step-by-step tutorial with hands-on exercise, troubleshooting, and next steps.

  5. 65
    Reproducible Random Seeds

    Learn to generate reproducible random seeds in Python for data science. This tutorial covers the core concept, hands-on steps, troubleshooting, and what to study next.

  6. 66
    NumPy Linear Algebra Basics

    Master linear algebra with NumPy: vector math, dot products, matrices, and solving systems. Hands-on code, troubleshooting, and next steps.

  7. 67
    Solve Equations with NumPy linalg

    Use NumPy's linalg module to solve systems of linear equations. Learn the key functions, see a hands-on example, and know when to choose each method. Part of our step-by-step Python for data science track.

  8. 68
    Pandas Correlation Analysis

    Learn how to perform correlation analysis in pandas with hands-on steps and troubleshooting tips.

  9. 69
    Test Hypotheses with SciPy

    Test hypotheses with scipy stats — a concise Python for data science lesson. Learn core concepts, step-by-step methods, and hands-on exercises to apply statistical testing in your data workflows.

  10. 70
    t-Tests & Chi-Square

    Run t-tests and chi-square tests in Python for data science. Hands-on steps, troubleshooting, and what to study next.

  11. 71
    Build simple linear regression models

    Learn to build simple linear regression models in Python for data science: core concepts, hands-on steps, and troubleshooting — lesson 43.

  12. 72
    R-squared for Regression

    Learn how to evaluate regression models using R-squared in Python for data science. This lesson explains the concept, walks through hands-on code, covers troubleshooting, and points to what to learn next.

    Python for data science — step-by-step tutorials

    What you will find here

    This track walks through python for data science in order — each lesson is server-rendered HTML you can read without JavaScript. Follow the outline, then practice in the browser IDE when a lesson links to runnable code.

    Tutorials vs quizzes and code samples

    Tutorials teach in sequence. For quick checks use quizzes. For copy-paste snippets see code samples. For deeper reading browse articles.