AI+ Vibe Coding Practitioner™

Course code: NPAP111

Formerly known as AI+ Vibe Coder™

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

Formerly known as AI+ Vibe Coder™
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

Professional
and certified lecturers

Internationally
recognized certifications

Wide range of technical
and soft skills courses

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service

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exactly to measure your needs

Course dates

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 4 hours

Language: en

Price without VAT: 285 EUR

Register

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 4 hours

Language: en

Price without VAT: 75 EUR

Register

Starting
date
Place
Type Course
duration
Language Price without VAT
G Upon request Self-paced 4 hours en 285 EUR Register
G Upon request Self-paced 4 hours en 75 EUR Register
G Guaranteed course

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Course description

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.

Course structure

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

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.

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