Opleiding: AI+ Vibe Coding Practitioner™

Supercharge coding with AI+ Vibe Coding Practitioner™ for smarter, faster creation

* 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

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 Tools you will explore

* 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)

Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam



Access to all materials and exams is provided for 365 days after delivery.

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