Course Prerequisites:
Basic Computer Skills – Comfortable with operating systems and files.
Mathematics Fundamentals – Understanding of algebra and basic statistics.
Logical Thinking – Ability to approach problems step by step.
Programming Curiosity – Interest in learning coding from scratch.
English Proficiency – Ability to follow technical instructions clearly.
Modules:
Module 1: Introduction to Vibe Coding & AI Tools
1.1 What is Vibe Coding?
1.2 Evolution of AI in Software Development – Low Code vs No Code vs Vibe Coding
1.3 Overview of Common AI Coding Tools by Functionality
1.4 SDLC for a Vibe Coding Product
1.5 Hands-on Lab: Familiarizing Learners with Multiple AI Coding Tools
1.6 Case Studies
Module 2: Prompting for Code – Basic and Best Practices
2.1 Anatomy of a Good Prompt
2.2 Prompt Types – Instructive, Descriptive, Iterative
2.3 Prompting Patterns – Zero-Shot, Few-Shot, Chain-of-Thought
2.4 Hands-on Lab: Practice Zero-Shot, Few-Shot, and Chain-of-Thought Prompting
2.5 Use-Cases
2.6 Assignment (Task) for Self-learning
Module 3: Debugging & Testing via AI
3.1 Reviewing and Refining AI-generated Code
3.2 Prompting for Bug Fixes and Test Coverage
3.3 Using AI-generated Unit Testing
3.4 Detecting Hallucinations and Unsafe Code
3.5 Hands-on Lab: AI-Assisted Debugging and Unit Testing
3.6 Activity Section
Module 4: Building a Simple Full-Stack App with Prompts
4.1 Planning the App: Frontend + Backend
4.2 Using IDEs and Code Generators to Scaffold Code
4.3 Connecting Components Using Natural Language
4.4 Deploying and Testing the MVP in Simulated Environment
4.5 Hands-on Lab: Building and Connecting the Frontend and Backend for Contact Form
4.6 Hands-on Lab: Building a Standalone Desktop Calculator Application Using Tkinter
4.7 Assignment and Task (Self-learning)
Module 5: Code Ethics, Security, and AI Limits
5.1 AI Limitations and Biases
5.2 Prompt Injection and Mitigation Strategies
5.3 Data Privacy and Secure Coding (Non-Technical Focus)
5.4 Responsible Use of AI in Production
5.5 Hands-on Lab: Build Awareness of AI Limitations and Responsible Practices
Module 6: Capstone Project – Prompt-Driven App
6.1 Apply All Learned Skills in a Real-World Project
6.2 Collaborate and Iterate Using AI Tools
6.3 Demonstrate End-to-End Development Using Prompts
6.4 Capstone Project Use Case: AI-Powered To-Do List Application
6.5 Capstone Project Use Case: AI-Powered Note-Taking Desktop App
6.6 Assignment and Task (Self-learning)
6.7 Use Case