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AI+ Vibe Coder™

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
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Certificate Code

AP 111

Exam Format

AI-Driven Remote Exam Proctoring

Course Overview

Important details and certification information

Instructor-led OR Self-paced course + Official exam + Digital badge
Instructor-Led: 3 Days (live or virtual)
Basic Computer Skills, Understanding of algebra and basic statistics, Logical Thinking, Programming Curiosity, English Proficiency
50 questions, 70% passing, 90 minutes, online proctored exam

Certification Modules

  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

  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

  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

  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

  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

  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 Tools Covered

Python
TensorFlow
PyTorch
GitHub Copilot
OpenAI Codex
Hugging Face Hub
LangChain
FastAPI
VS Code
Jupyter Notebooks
Pandas
NumPy
Scikit-learn
Docker
Streamlit
API Integration Tools
Prompt Engineering Frameworks
Automation SDKs
Version Control Systems (Git)
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