• Beginner-Friendly Approach: Designed for aspiring creators eager to explore AI-assisted coding with ease and confidence
• Interactive Learning Journey: Blends core coding concepts, intuitive AI tools, and hands-on practice to build real problem-solving skills
• Project-Driven Growth: Provides guided exercises and practical projects to help you build, refine, and showcase your AI-powered coding talents

Module 1: Introduction to Vibe Coding & AI Tools

1. 1.1 What is Vibe Coding?
2. 1.2 Evolution of AI in Software Development – Low Code vs No Code vs Vibe Coding
3. 1.3 Overview of Common AI Coding Tools by Functionality
4. 1.4 SDLC for a Vibe Coding Product
5. 1.5 Hands-on Lab: Familiarizing Learners with Multiple AI Coding Tools
6. 1.6 Case Studies

Module 2: Prompting for Code – Basics & Best Practices

1. 2.1 Anatomy of a Good Prompt
2. 2.2 Prompt Types – Instructive, Descriptive, Iterative
3. 2.3 Prompting Patterns – Zero-Shot, Few-Shot, Chain-of-Thought
4. 2.4 Hands-on Lab: Practice Zero-Shot, Few-Shot, and Chain-of-Thought Prompting
5. 2.5 Use-Case 1: Creating a Python Calculator
6. 2.6 Use-Case 2: Optimizing AI-generated Code Using Different Prompt Types

Module 3: Debugging & Testing via AI

1. 3.1 Reviewing and Refining AI-generated Code
2. 3.2 Prompting for Bug Fixes and Test Coverage
3. 3.3 Using AI-generated Unit Testing
4. 3.4 Detecting Hallucinations and Unsafe Code
5. 3.5 Hands-on Lab: AI-Assisted Debugging and Unit Testing
6. 3.6 Activity Section

Module 4: Building a Simple Full-Stack App with Prompts

1. 4.1 Planning the App: Frontend + Backend
2. 4.2 Using IDEs and Code Generators to Scaffold Code
3. 4.3 Connecting Components Using Natural Language
4. 4.4 Deploying and Testing the MVP in Simulated Environment
5. 4.5 Hands-on Lab: Building and Connecting the Frontend and Backend for Contact Form Submission
6. 4.6 Hands-on Lab: Building a Standalone Desktop Calculator Application Using Tkinter
7. 4.7 Hands-on Assignment 1: Task Management System – Full-Stack Development Using Prompts

Module 5: Code Ethics, Security, and AI Limits

1. 5.1 AI Limitations and Biases
2. 5.2 Prompt Injection and Mitigation Strategies
3. 5.3 Data Privacy and Secure Coding
4. 5.4 Responsible Use of AI in Production
5. 5.5 Hands-on Lab: Build Awareness of AI Limitations and Responsible Practices

Module 6: Capstone Project – Prompt-Driven App

1. 6.1 Apply All Learned Skills in a Real-World Project
2. 6.2 Collaborate and Iterate Using AI Tools
3. 6.3 Demonstrate End-to-End Development Using Prompts
4. 6.4 Capstone Project Use Case: AI-Powered To-Do List Application
5. 6.5 Capstone Project Use Case: AI-Powered Note-Taking Desktop App
6. 6.6 Assignments

AI Software Developer

Design and build intelligent applications that leverage machine learning models to automate processes and enhance user experiences.

Data-Driven Application Developer

Develop smart apps powered by data analytics and predictive modeling to solve real-world business challenges.

Automation Solutions Architect

Create AI-based automation pipelines that streamline coding workflows, boost productivity, and reduce manual effort.

Chief AI Innovation Engineer (CAIIE)

Lead next-generation AI software initiatives, driving digital transformation and intelligent product development across industries.