Course 2 — The Rising Builders

Format: live online · Sessions: 22 × 75 min

The learning path:

Welcome to The Rising Builders — where you write real code and build serious projects: machine-learning models, a smart gadget, web apps and more. Each lesson gives you something to learn, live code to run, a project to build, and challenges to push yourself. Open any lesson below to see exactly what you'll do.

What the course covers

1. Unit 1 — Applied AI & Data Science (Sessions 1–4): Python, working with datasets, building a prediction model, and what AI can and can't do.
2. Unit 2 — Research & Engineering (Sessions 5–8): how real research works, reading and writing science, and building electronics with Arduino.
3. Unit 3 — Competition & Portfolio (Sessions 9–12): turning work into a competition entry, a written report with peer review, and a final presentation.
4. Bonus — Generative AI (Sessions 13–14): how LLMs work, and building with generative AI responsibly.
5. Unit 4 — Build a Web App (Sessions 15–18): HTML, CSS & JavaScript to build and deploy a real web app.
6. Unit 5 — Deeper AI (Sessions 19–22): computer vision and NLP mini-projects in Python.

What students produce

• A working prediction model and a small data-science project.
• A research report + an engineered/data prototype.
• A competition-ready project and a portfolio piece, plus a course certificate.

Soft skills — the human side of tech

Coding is only half the job. Every session also carries a Soft skill focus — it names one human skill, gives you a concrete way to grow it during the activity, and ends with a short reflection at the wrap-up. Across the course, students practise all eight of the skills that every tech career needs:

Look for the Soft skill focus box near the top of each session — it tells you which skill to grow that day, and exactly how.

Tools (all free)

Google Colab (Python in the browser) · Tinkercad Circuits (Arduino, no hardware) · Google Sheets · free datasets — the exact links are in each session's Resources.

How each lesson works

Every lesson follows the same flow: What you'll need → learn it → your turn (build it, with code you type and run yourself) → check yourself (questions with the answers) → a wrap-up and a try-at-home idea → then Tips & extra challenges, Vocabulary and Resources. Watch for the ⚠ Watch out notes — they flag the common mistakes before they trip you up.

Sessions

Unit 1 — Applied AI & Data Science

1. Session 1 — Speak Python
2. Session 2 — Playing with Data
3. Session 3 — Your First Prediction
4. Session 4 — What AI Can (and Can't) Do

Unit 2 — Research & Engineering

1. Session 5 — Think Like a Scientist
2. Session 6 — Read Like a Scientist
3. Session 7 — Hello, Hardware!
4. Session 8 — Build a Smart Gadget

Unit 3 — Competition & Portfolio

1. Session 9 — Enter the Arena
2. Session 10 — Polish Your Project
3. Session 11 — Write It Up & Peer Review
4. Session 12 — Showtime! (Final Showcase)

Bonus — Generative AI

1. Session 13 — How Generative AI Works
2. Session 14 — Build with Generative AI

Unit 4 — Build a Web App

1. Session 15 — The Web Stack
2. Session 16 — Make It Interactive
3. Session 17 — Build a Real App
4. Session 18 — Ship It

Unit 5 — Deeper AI

1. Session 19 — How Machines See
2. Session 20 — Build an Image Classifier
3. Session 21 — How Machines Read
4. Session 22 — Your AI Mini-Project & Showcase

Projects & Assessment

Each unit ends with a hands-on project + grading rubric, and the course finishes with a portfolio-ready capstone.

• Unit 1 Project — Build a Predictor
• Unit 2 Project — Research & Build
• Unit 3 Project — Competition Entry
• Course Capstone — Research & Innovation Project
• Certificate & Assessment Criteria

Ready? Open Session 1 — Speak Python