AI+ Vibe Coder™ – Course Outline
Program Overview
The AI+ Vibe Coder™ certification is designed to equip learners with modern AI-assisted coding skills, enabling them to build software applications faster, smarter, and more efficiently using Artificial Intelligence tools and workflows. The course focuses on the emerging “vibe coding” approach, where developers collaborate with AI systems to generate, optimize, debug, and deploy code through natural language prompts and intelligent automation.
Participants will explore practical applications of AI in software development, including prompt engineering for coding, AI pair programming, automated debugging, code generation, workflow automation, rapid prototyping, API integration, and low-code/no-code development enhancement. The program combines theory, demonstrations, and hands-on exercises to help learners confidently use AI-powered coding environments in real-world projects.
Course Objectives
By the end of this course, participants will be able to:
• Understand the fundamentals of AI-assisted software development
• Use AI coding assistants for code generation and debugging
• Apply prompt engineering techniques for development tasks
• Build applications using AI-powered workflows
• Integrate APIs and automation tools into projects
• Improve coding productivity using AI collaboration tools
• Develop rapid prototypes and MVP applications
• Implement ethical and secure AI coding practices
• Optimize software testing and documentation using AI
• Deploy AI-assisted applications efficiently
Target Audience
• Beginner and intermediate software developers
• Web and mobile application developers
• AI enthusiasts and technology professionals
• Low-code/no-code developers
• Startup founders and product builders
• Students pursuing software engineering or AI careers
• IT professionals seeking AI productivity skills
• Freelancers and digital creators
Course Duration
- Instructor-Led: 1 day (live or virtual)
- Self-Paced: 8 hours of content
Assessment & Certification
• Module-based quizzes and assessments
• AI-assisted coding exercises
• Practical software development activities
• Mini-project submissions
• Final capstone development project
Certification:
Participants will receive the AI+ Vibe Coder™ Certification upon successful completion.
Training Methodology
• Instructor-led sessions (virtual/classroom)
• Hands-on coding workshops
• AI tool demonstrations
• Project-based learning
• Interactive development labs
• Real-world coding scenarios and exercises
Course Modules
Module 1: Introduction to Vibe Coding & AI Tools
• What is Vibe Coding?
• Evolution of AI in software development – Low Code vs No Code vs Vibe Coding
• Overview of common AI coding tools by functionality
• SDLC for a Vibe Coding product
• Hands-on lab: Familiarizing learners with multiple AI coding tools
• Case studies
Module 2: Prompting for Code – Basics & Best Practices
• Anatomy of a good prompt
• Prompt types – Instructive, descriptive, iterative
• Prompting patterns – Zero-shot, few-shot, chain-of-thought
• Hands-on lab: Practice zero-shot, few-shot, and chain-of-thought prompting
• Use-case: Creating a Python calculator
• Use-case: Optimizing AI-generated code using different prompt types
Module 3: Debugging & Testing via AI
• Reviewing and refining AI-generated code
• Prompting for bug fixes and test coverage
• Using AI-generated unit testing
• Detecting hallucinations and unsafe code
• Hands-on lab: AI-assisted debugging and unit testing
• Activity section
Module 4: Building a Simple Full-Stack App with Prompts
• Planning the application: Frontend and backend
• Using IDEs and code generators to scaffold code
• Connecting components using natural language
• Deploying and testing the MVP in a simulated environment
• Hands-on lab: Building and connecting frontend and backend for contact form submission
• Hands-on lab: Building a standalone desktop calculator application using Tkinter
• Hands-on assignment: Task management system – Full-stack development using prompts
Module 5: Code Ethics, Security, and AI Limits
• AI limitations and biases
• Prompt injection and mitigation strategies
• Data privacy and secure coding practices
• Responsible use of AI in production
• Hands-on lab: Building awareness of AI limitations and responsible practices
Module 6: Capstone Project – Prompt-Driven App
• Apply all learned skills in a real-world project
• Collaborate and iterate using AI tools
• Demonstrate end-to-end development using prompts
• Capstone project use-case: AI-powered To-Do List application
• Capstone project use-case: AI-powered note-taking desktop application
• Assignments
