Course Overview

The AI+ Vibe Coder certification equips learners with essential skills to thrive in the evolving world of artificial intelligence and coding. Designed for beginners and professionals seeking foundational knowledge, the program emphasizes core AI concepts, coding practices, and ethical applications. Participants gain hands-on experience with AI tools, algorithms, and problem-solving techniques to build practical solutions. The certification fosters critical thinking, creativity, and collaboration, ensuring graduates are prepared for future opportunities in AI-driven industries. By completing this program, learners demonstrate their readiness to contribute effectively to projects that combine innovation, technical skills, and responsible AI development

Program Objectives

By the end of the training, participants will be able to:

• Learn AI-Assisted Software Development: Understand how to use AI tools to design, write, and improve code more efficiently.
• Build Applications Faster: Gain hands-on experience developing functional applications using AI-powered coding assistants and no-code/low-code tools.

Who Should Join?

This training is ideal for: 

• Software Developers, IT professional & Technical Teams, Tech Enthusiast, Beginner

Pre-requisite

• 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

Course Outline 

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 Submission

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