MetaCyberGuru Academy
Build a reproducible Python workspace, inspect real datasets and reason about distributions, distance and similarity.
Module result: Project: Build a Dataset Profiler in Python.
Why this module belongs in the course
A working notebook is not automatically a reproducible analysis. The environment, random state, data version and commands must be recorded so a second person can reproduce the result.
Before you begin
The concepts and project evidence from Module 1. You should also be able to create a Python virtual environment and keep private or employer data out of the exercise.
Four lessons, one connected result
- Lesson 1Set Up Python for Reproducible Data Mining55 min · Beginner
- Lesson 2Understand Data with Distributions, Sampling and Robust Statistics65 min · Beginner
- Lesson 3Distance and Similarity Measures for Data Mining70 min · Beginner to intermediate
- Lesson 4Project: Build a Dataset Profiler in Python100 min · Beginner to intermediate
How to know you are ready to continue
Complete the checkpoint without copying the worked example. Keep the code, output and a short decision note. Your note should explain one choice, one failure you observed and one limitation a reviewer should know.
Primary references for this module
The lessons explain the ideas in original wording. Use these primary or official sources when a library interface, standard or research claim needs verification.
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