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CS 102: Rapid Web Development for AI Products
Course Code CS 102
Course Name Rapid Web Development for AI Products
Department Computer Science
Semester Offered Odd (Term 1 - Dubai)
Tuition Hours 30 hours
Course Level Foundational
Pre-requisite CS 101: Introduction to Computational Thinking
Co-requisite -
Course Objective Ideas are cheap. Distribution is hard. And in the age of AI, the fastest way to test an idea is to ship a working product to real users.

This course teaches students how to go from a raw idea to a deployed AI product in the shortest possible time. The focus is not on mastering frameworks, but on understanding how the pieces fit together: frontend, backend, APIs, and deployment.

Students will learn to build full-stack applications using modern tools like React and FastAPI, integrate AI capabilities, and deploy their products to the internet. By the end of the course, they will be able to launch usable products in hours, not weeks.

The goal is simple: if you can build it, you should be able to ship it the same day.
Course Philosophy This course emphasizes
  • Shipping over polishing
  • Understanding systems over memorizing frameworks
  • Learning by building real products
Students will not be taught everything. Instead, they will learn just enough to build, break, debug, and iterate. The goal is to develop the confidence that no stack is intimidating once you understand the fundamentals.
Course Learning Outcomes Upon successful completion of this course, students will be able to:
  • Design simple and functional user interfaces with a clear understanding of user experience.
  • Build frontend applications using component-based architecture and basic state management.
  • Develop backend APIs to handle data processing and AI model interactions.
  • Connect frontend and backend systems into a working full-stack application.
  • Integrate AI APIs and models into real products that users can interact with.
  • Deploy applications to production using modern hosting platforms.
  • Debug across the stack, from UI issues to backend failures.
  • Ship and iterate on a real AI product, contributing directly to their Term 1 microbusiness agent.
Course Author Sagar Udasi
MSc Statistics and Data Science with Computational Finance from The University of Edinburgh.
Contact: sagar.l.udasi@gmail.com
Course Organiser TBD
Details will be updated before course commencement.
No. Lecture Title Concepts Covered Lecture Objective
01 What Even Is A Product? Product thinking, users, value Shift mindset from coding to building something people actually use.
02 The Simplest Website That Works HTML basics, structure, rendering Ground students in how the web actually works before abstractions.
03 From Static To Interactive Intro to React, components Introduce component-based thinking for scalable UI systems.
04 Why Your UI Feels Broken State, reactivity, data flow Teach how UI changes over time. Critical for interactive apps.
05 Pages, Routes, and Navigation Routing, layouts in Next.js Help students structure multi-page applications.
06 Design That Doesn’t Annoy Users UI/UX basics, usability Build products people can actually use without friction.
07 Where Does The Data Come From? APIs, client-server model Introduce backend necessity and data flow.
08 Building Your First Backend FastAPI basics, endpoints Students create APIs that power their applications.
09 Connecting Frontend To Backend Fetching data, async calls Combine systems into a working full-stack app.
10 Your App Can Talk To AI Now AI API integration Directly enables AI-powered product features.
11 Handling Real Users (Not Ideal Ones) Validation, error handling Prepare for messy real-world usage.
12 Authentication Without Overthinking Basic auth flows Enable user-specific experiences in products.
13 Storing Things That Matter Databases (intro), persistence Teach how products remember users and actions.
14 Why Your App Is Slow Performance basics, optimization Improve responsiveness and user experience.
15 From Localhost To The Internet Deployment basics, Vercel, Railway Students deploy their first live product.
16 Debugging Across The Stack Logs, network errors, debugging tools Teach how to fix real issues in production systems.
17 Building Fast Without Breaking Things Rapid prototyping, iteration Instill speed with control.
18 Turning Features Into Products Product refinement, feedback loops Help students move from features to usable systems.
19 Scaling From 10 Users To 1000 Basic scaling, reliability Prepare for their Term 1 goal of 1000 users.
20 Demo Day: Ship Or It Doesn’t Count Product demos, critique Enforce shipping culture. Students present live products.
Component Weightage
Weekly Build Assignments (4 total) 30%
Full-Stack Mini Project 20%
Final Project: Deployed AI Product 30%
Live Demo + Code Review 20%
Type Resource Provider
Lecture React Crash Course Traversy Media
Lecture Next.js Documentation Vercel
Lecture FastAPI Tutorial Sebastián Ramírez
Reading Full Stack Open University of Helsinki
Practice Buildspace Projects buildspace.so