AI+ Vibe Coder
Supercharge coding with AI+ Vibe Coder™ for smarter, faster creation.
Description
- 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
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.
Course Outline
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 Coding1.3 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 1: Creating a Python Calculator
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 1: Creating a Python Calculator
Use-Case 2: Optimizing AI-generated Code Using Different Prompt Types
Module 3: Debugging & Testing via AI
Reviewing and Refining AI-generated CodePrompting 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 App: Frontend + Backend
Using IDEs and Code Generators to Scaffold Code
Connecting Components Using Natural Language
Deploying and Testing the MVP in Simulated Environment
Hands-on Lab: Building and Connecting the Frontend and Backend for Contact Form Submission
Hands-on Lab: Building a Standalone Desktop Calculator Application Using Tkinter
Hands-on Assignment 1: Task Management System – Full-Stack Development Using Prompts
Prompt Injection and Mitigation Strategies
Data Privacy and Secure Coding
Responsible Use of AI in Production
Hands-on Lab: Build Awareness of AI Limitations and Responsible Practices
Using IDEs and Code Generators to Scaffold Code
Connecting Components Using Natural Language
Deploying and Testing the MVP in Simulated Environment
Hands-on Lab: Building and Connecting the Frontend and Backend for Contact Form Submission
Hands-on Lab: Building a Standalone Desktop Calculator Application Using Tkinter
Hands-on Assignment 1: Task Management System – Full-Stack Development Using Prompts
Module 5: Code Ethics, Security, and AI Limits
AI Limitations and BiasesPrompt Injection and Mitigation Strategies
Data Privacy and Secure Coding
Responsible Use of AI in Production
Hands-on Lab: Build 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 App
Assignments
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 App
Assignments