Eight lectures in weeks 1–8, workshops in weeks 2–11. A lecture introduces a topic and the following week's workshop practises it — so Lecture 1 is worked through in the week 2 lab.
Lecture 1: Data Types, Variables and Basic Operations
Lecture 2: From One Sequence to Many: Lists, Strings & Maps
Lab 1: Setup & First Steps
Lecture 3: Control Flow: Teaching a Program to Run Itself
Lab 2: Lists, Strings & Maps
Lecture 4: Algorithms, Functions & Defensive Programming
Lab 3: Loops, Logic & VS Code
Lecture 5: Arrays — One Neuron, Many Trials
Lab 4: Functions, Errors & Files
Test (15%) — sat in this workshop
Lecture 6: DataFrames — Who Pollinates Your Dinner?
Lab 5: Arrays, numpy & Projects
Lecture 7: Plotting — Making Data Visible
Lab 6: Explorative Data Analysis
Project 1 due (15%)
Lecture 8: LLMs & Agentic AI
Lab 7: End-to-End Data Mining
Lab 8: LLMs & Agentic AI
Workshop: Project workshop
Workshop: Project workshop
Project 2 due (70%)
| Week | Lecture | Workshop | Project time | Assessment |
|---|---|---|---|---|
| 1 | 1. Data Types, Variables and Basic Operations | — | ||
| 2 | 2. From One Sequence to Many: Lists, Strings & Maps | Lab 1. Setup & First Steps | ||
| 3 | 3. Control Flow: Teaching a Program to Run Itself | Lab 2. Lists, Strings & Maps | ||
| 4 | 4. Algorithms, Functions & Defensive Programming | Lab 3. Loops, Logic & VS Code | Project 1 | |
| 5 | 5. Arrays — One Neuron, Many Trials | Lab 4. Functions, Errors & Files | Project 1 | Test (15%) — sat in this workshop |
| 6 | 6. DataFrames — Who Pollinates Your Dinner? | Lab 5. Arrays, numpy & Projects | Projects 1 & 2 | |
| 7 | 7. Plotting — Making Data Visible | Lab 6. Explorative Data Analysis | Projects 1 & 2 | Project 1 due (15%) |
| 8 | 8. LLMs & Agentic AI | Lab 7. End-to-End Data Mining | Project 2 | |
| 9 | — | Lab 8. LLMs & Agentic AI | Project 2 | |
| 10 | — | Project workshop | Project 2 | |
| 11 | — | Project workshop | Project 2 | Project 2 due (70%) |
20–30 minute topic blocks, each with a basic and an advanced notebook. Exercises are a mix of writing code, debugging it, and reading it.
The labs also build the tooling around the code: terminal, uv, VS Code, GitHub repositories and commits, and keeping a project tidy.
Workshop time is set aside for the projects — Project 1 from week 4, Project 2 from week 6 — so you are never doing them entirely alone.
Deadlines and submission are on Canvas. See Assessment for what each piece involves.