Python, SQL & Data Science
One programme, three disciplines, built in the order you actually need them: write Python, query data properly, then use both to answer real questions with real datasets.
- Duration
- 16 weeks
- Format
- Live online + recordings
- Commitment
- 6–8 hrs / week
- Cohort size
- Capped at 25
Curriculum
- 01
Python Foundations
Syntax, data structures, functions, files, error handling and clean code habits. By the end you are writing scripts, not following along.
- 02
SQL & Databases
SELECT through window functions: joins, aggregations, CTEs, indexing and schema design on PostgreSQL, using messy real-world data.
- 03
Data Analysis
NumPy, pandas and the whole cleaning-reshaping-merging grind, then visualisation with Matplotlib and Seaborn that communicates rather than decorates.
- 04
Statistics & Machine Learning
Distributions, hypothesis testing, regression and classification with scikit-learn — plus how to tell when a model is lying to you.
- 05
Working Like an Analyst
Git, notebooks to production, APIs and scraping, dashboarding, and framing a business question so the analysis answers something worth asking.
- 06
Capstone Project
Pick a domain, source the data, build the analysis end to end, and present it. You leave with a portfolio piece and a repo you can defend in an interview.
What you leave with
- Write production-quality Python without a tutorial open
- Query and model data in SQL with confidence
- Build a full analysis from raw data to a defensible conclusion
- Ship three portfolio projects and one capstone
- Interview prep, résumé review and mock technical rounds
Who it is for
- Graduates targeting analyst and data roles
- Working professionals moving into data
- Founders and operators who want to stop asking someone else for numbers