What to Expect in Your First Month as a Fellow
You've been accepted. You've signed the agreement. Now what? Here's what your first month in the Gradient Fellows fellowship actually looks like.
Week 1: Orientation and Setup
Your first week is about getting set up and aligned with your mentor.
- Day 1-2: Welcome call with the programme founder. You'll discuss your background, your goals, and what you hope to build.
- Day 3-4: Environment setup. Python, Jupyter, Git, VS Code. Your mentor will help you through any blockers.
- Day 5: First mentor 1:1. This is where you'll map out your first month's learning path together.
Week 2: Mathematics Refresher
Even if your maths is strong, we spend a week making sure your foundations are solid for ML specifically.
- Linear algebra review with a focus on matrix operations, eigenvalues, and SVD
- Probability and statistics with an ML lens (Bayes, distributions, hypothesis testing)
- Calculus refresher focused on gradients and optimisation
This isn't busywork. Every concept maps directly to something you'll use in Week 3.
Week 3: Your First ML Model
This is the week most fellows remember. You'll build your first machine learning model from scratch.
- Understanding the ML pipeline: data → features → model → evaluation
- Implementing linear regression and logistic regression from scratch (not just calling sklearn)
- Training your first neural network on a real dataset
- Learning to read and interpret loss curves, confusion matrices, and evaluation metrics
Week 4: Your First Deliverable
Month 1 ends with your first deliverable: a complete, documented ML project on GitHub.
- Choose a dataset relevant to your STEM background
- Build a model that solves a real (if simple) problem
- Write a clear README explaining your approach and results
- Push to GitHub. This is the first piece of your portfolio.
Your mentor reviews the deliverable. If it meets the bar, your first month's stipend is released.
The Rhythm
After Month 1, you'll have established a rhythm: learn, build, deliver, repeat. The content gets harder, the projects get more ambitious, and your portfolio grows. But the structure stays the same.
That's the whole point. Structure turns motivation into momentum.

