Course Overview
TOPAI+ Vibe Coding Practitioner™ delivers an end-to-end technical understanding of prompt-driven software development. Participants learn structured prompting, AI-powered debugging, automated testing, and the use of multiple AI coding tools across SDLC phases.
The program features hands-on labs where learners build Python utilities, GUI applications, and full-stack systems using natural language instructions. Topics include prompt engineering patterns, responsible coding, prompt injection risks, secure code practices, and model limitations, providing practical expertise for applying AI across development workflows and accelerating engineering efficiency.
Scheduled Classes
TOP| 07/10/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 08/07/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 09/04/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 10/09/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 11/06/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 12/04/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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What You'll Learn
TOP- Understand vibe coding concepts and the role of AI tools in software development
- Write effective prompts for generating, optimizing, and debugging code
- Build Python utilities, GUI apps, and simple full-stack prototypes using AI-driven workflows
- Use AI to perform unit testing, code review, and safe debugging
- Apply secure coding, ethical practices, and prompt injection mitigation strategies
Outline
TOPIntroduction 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
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
- Use-Case 2: Optimizing AI-generated Code Using Different Prompt Types
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
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
Code Ethics, Security, and AI Limits
- AI Limitations and Biases
- 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
Prerequisites
TOPRequired
- 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
- English Proficiency – Ability to follow technical instructions clearly
- Programming Curiosity – Interest in learning coding from scratch
Who Should Attend
TOP- Software Developer
- Programmer
