Live Class 1: What is SQA & The AI Revolution in QA
What is Software Quality Assurance | Why SQA is important in SDLC | Difference between QA, QC & Testing | Objectives of SQA | Software Quality Factors | How AI is reshaping the QA landscape | AI-powered testing tools overview (Claude Code, GitHub Copilot, Playwright AI) | Overview of AI-assisted vs fully automated QA | SQA in Agile & AI-first development models | Real-life examples of AI catching bugs faster

Live Class 2: Roles, Responsibilities & AI Career Path in SQA
Emerging roles: AI QA Engineer, Prompt Engineer for Testing, AI Quality Lead | Day-to-day tasks with AI tools | Skills required: coding + AI prompting + traditional QA | Career path from Junior QA to AI Quality Engineer | Certifications (ISTQB AI Testing, CSTE, etc.) | AI tools ecosystem for QA professionals | Freelancing in the AI-QA era | How AI-augmented QA teams collaborate with Developers & PMs | Real-world AI-QA career roadmap

Live Class 1: Flow of STLC | AI-Assisted Problem Statement Identification

What is STLC | Difference between SDLC & STLC | Phases of STLC (Requirement Analysis → Test Closure) | QA involvement in each phase | Using AI (Claude, ChatGPT) to understand the application under test | How to identify the problem statement with AI assistance | AI-driven early bug detection strategies | Importance of early testing with AI co-pilot support

Live Class 2: AI-Assisted Test Plan & Test Case Design | Test Checklist Generation
What is a Test Plan | Key elements of a test plan | Writing Test Plans with Claude Code assistance | Introduction to AI-generated Test Cases | How to prompt AI to write effective test cases (title, steps, expected result) | AI-generated Test Checklists | Reviewing and refining AI outputs | Manual vs AI-generated template comparison

Live Class 3: AI-Powered Test Case Review and Analysis

Live Class 4: Defect Tracking with AI | Intelligent Test Cycle Closure

Live Class 1: Flow of SDLC | Waterfall Model & AI Integration Points
What is SDLC | Importance of SDLC in software projects | Phases of SDLC (Requirement Analysis, Design, Implementation, Testing, Deployment, Maintenance) | Flow of each phase with real-life examples | Waterfall Model: Structure and Characteristics | Pros and Cons of Waterfall | Where AI assists in each SDLC phase | AI-powered requirement analysis tools | QA involvement in Waterfall | Limitations of sequential models in AI-driven projects

Live Class 2: Agile Process | Scrum | AI-Augmented Development Workflows
Why Agile? | Agile Manifesto & Principles | Agile vs Waterfall | Key Agile methodologies (Scrum, Kanban) | Scrum Framework with AI tooling | Scrum Roles in AI-enabled teams | Scrum Ceremonies with AI assistants (Sprint Planning with Copilot, Stand-ups with AI summaries) | Sprint Lifecycle | QA's role in AI-Agile teams | Using AI for continuous feedback and risk detection in sprints

Live Class 1: JavaScript Fundamentals with AI Assistance
Introduction to JavaScript: What is JavaScript and why it's important for QA | Setting up JavaScript environment with AI guidance | Understanding JavaScript syntax using Claude Code | Variables and Data Types in JavaScript | Introduction to ES6: Features (let/const, arrow functions, template literals) | Using Claude Code to explain and generate JS code snippets | Understanding ES6 modules (import/export) | Real-life examples: letting AI write boilerplate JS for testers

Live Class 2: Node.js with AI-Generated Code | OOP Basics
What is Node.js and how it works | Setting up Node.js environment with Claude Code | Running AI-generated JavaScript code with Node.js | Introduction to programming concepts via AI prompting (Variables, Functions, Loops, Conditionals) | Understanding OOP with AI-explained examples | Using Claude Code to debug Node.js scripts in real-time | Event-driven programming in Node.js explained by AI | Real-world example: AI-generated Node.js test helper scripts

Live Class 1: Git & GitHub with AI (Claude Code commits & PR generation)

Live Class 2: AI-Assisted Branching, Merging & Code Review with GitHub Copilot

Live Class 1: AI-Assisted Problem Analysis & Planning
How to break down a problem statement with AI co-pilot | Using Claude Code to identify input, output, and constraints | Understanding edge cases with AI suggestions | Drafting solution plans using AI-generated pseudocode or flowcharts | Real-life QA/test-related problem statements solved with Claude Code | Step-by-step AI prompting strategy: break → ask → refine → validate

Live Class 2: Translating AI Plans into Tested Code
Prompting Claude Code to translate logic plans into JavaScript | Live problem solving: AI generates, human reviews & tests | Walkthrough of AI-assisted logic writing, debugging, and test outputs | Practice: Conditional logic, loops, array handling — all with Claude Code | Evaluating AI code quality: when to accept, modify, or reject AI output | Students submit AI-assisted solutions for code review