AI+ Vibe Coder™

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

At a Glance: Course + Exam Overview

Category	AI Development AI Professional All Courses English Language Software Developer
Program Name	AI+ Vibe Coder™
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.
Exam Format	50 questions, 70% passing, 90 minutes

What You'll Learn

AI-Assisted Coding
Learn how to write, optimize, and debug code using intelligent AI tools and natural language interfaces.
Machine Learning Fundamentals
Understand core ML concepts to build smarter, data-driven applications that adapt and improve over time.
Generative Development Techniques
Explore how generative AI can automate code generation, testing, and creative problem-solving in real-world projects.
Ethical and Responsible Coding
Gain awareness of responsible AI practices, ensuring transparency, fairness, and safety in AI-powered software solutions.

Certification 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 – Basics & 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-Case 1: Creating a Python Calculator
2.6 Use-Case 2: Optimizing AI-generated Code Using Different Prompt Types

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 Hands-on Assignment 1: Task Management System – Full-Stack Development Using Prompts

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
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 Assignments

Industry Opportunities

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.

Frequently Asked Questions

Yes, this certification provides hands-on experience through real coding challenges and AI-driven projects. You’ll be ready to build intelligent applications and automate workflows from day one.

This certification uniquely combines programming fundamentals with AI-powered development, focusing on real-world automation, generative coding, and intelligent software creation.

You’ll work on projects like AI-assisted app development, automated code generation, chatbot creation, and a capstone project building an AI-powered coding assistant or tool.

The course blends expert-led lessons, interactive coding labs, and practical projects with real-world applications to ensure hands-on mastery of AI-integrated programming.

It equips you with high-demand AI coding skills, real-world project experience, and the technical foundation needed for emerging roles in AI software and automation development.

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.

Exam Details

Duration

90 minutes

Passing Score

70%

Format

50 multiple-choice/multiple-response questions

Exam Blueprint

Introduction to Vibe Coding & AI Tools	15%
Prompting for Code - Basics & Best Practices	15%
Debugging & Testing via AI	15%
Building a Simple Full-Stack App with Prompts	20%
Code Ethics, Security, and AI Limits	20%
Capstone Project - Prompt-Driven App	15%