DS · 03 · Semester course
Introduction to
Introduction to
Data Science
Data science is not a library you import. It is the discipline of taking a raw, awkward, incomplete file and turning it into something a person can actually decide with — and knowing, at every step, how much you are entitled to claim.
Content coming soon
Data to decisions
Government Graduate College, Layyah
Coming soon
The notes for this course
The notes for this course
are on their way.
This page is deliberately empty for now. I publish each lesson only after we have covered it in class, so that what you read here matches exactly what was taught — the same datasets, the same code, the same worked examples.
Keep this link. Check back after every session, and you will always find the latest material waiting here.
- What data science actually is — and the honest difference between it, statistics and analytics.
- Collecting and storing data — files, tables, formats, and where things go wrong first.
- Cleaning — missing values, duplicates, wrong types, and the unglamorous work that decides everything.
- Exploratory analysis — asking a dataset good questions before you assume any answers.
- Visualisation — charts that reveal rather than decorate, and the ones that mislead.
- A first model, and communicating it — a simple prediction, and how to present it without overclaiming.