Track 02 of 06
AI & Machine Learning
Learn applied machine learning the way teams use it: clean a dataset, train and evaluate a model honestly, and put it behind an API. Self-paced and free, with a peer pod and a volunteer mentor.
- Cost
- Free
- Pace
- Self-paced
- Builds toward
- Machine learning engineer
Is it for you?
You are comfortable with basic Python and want practical ML experience (evaluation, data quality, deployment), not only notebook exercises.
What you’ll learn
- Prepare and clean a realistic dataset, and document what you changed
- Choose a baseline and measure whether a model actually beats it
- Evaluate models with the right metrics, not only accuracy
- Serve a trained model behind an API that other code can call
- Write down a model’s limits so others can use it responsibly
The stack
- Python
- pandas
- scikit-learn
- PyTorch basics
- Model evaluation
- FastAPI
The project brief
Product recommendation engine
Train a recommendation model on a realistic sample of shop data, compare it against a simple popularity baseline, and serve its suggestions through an API a storefront could call.
- What it shows
- That you can take a model from raw data to something usable, and explain honestly how well it works.
- Builds toward
- Machine learning engineer
Briefs are modelled on real startup problems for learning. The work is yours: it is not done for any company, and it is not paid.
How the track runs
- Plant roots. Create your profile, choose your track and see what it covers.
- Foundations. Work through your track’s learning material at your own speed.
- Project sprint. Join a pod of up to six and build a production-style project brief.
- Lead and reflect. Optionally lead a pod, support newer students, and review what you learned.
- Share your portfolio. Publish your shipped work and earn your certificate of completion.
Questions about this track
- How much maths do I need for the AI & Machine Learning track?
- Enough to follow what a model is doing: basic algebra and some statistics. The track focuses on applied skills and fills gaps as they come up.
- Do I need a powerful computer to train models?
- No. The project uses datasets and models sized for an ordinary laptop or a free hosted notebook.
Plant your roots
Create a free account, choose your track and start at your own pace. No card needed, and you can pause or leave at any time.