Step-by-step guides
Learn Python, SQL & Data Analytics by Doing
Walkthroughs that explain fundamental concepts with clear, reproducible code snippets, written from the perspective of a student working through the same challenges.
Learning tracks
Three foundations, one practical path
Each track breaks complex math and programming libraries into digestible steps you can follow and reproduce.
Track 01
Python Fundamentals
Syntax, control flow, functions, and the core libraries used in everyday data work, introduced one concept at a time.
Track 02
SQL Query Mechanics
How joins, aggregations, and filters behave on real tables, with small datasets you can run and change yourself.
Track 03
Exploratory Data Analytics
Cleaning, summarising, and visualising a dataset to ask better questions before any modelling begins.
How tutorials are written
Reproducible code, explicit versions
Every tutorial is built in a notebook that runs top to bottom. Library versions are stated plainly, so a reader can recreate the same results on their own machine without guessing what changed.
The guides also record the real snags I hit during coursework and side projects, along with how I got past them. Where an approach did not work, I say so, because that is often the most useful part for a learner following along.