ব্যাচের কার্যক্রম - মেইন লাইভ ক্লাস শুরুর আগেই যারা ইনরোল করেছেন, তারা কি বসে থাকবেন ? না! এই মডিউলে ব্যাসিক বেশ কিছু ভিডিও দেওয়া আছে। শুরু হয়ে যাক তবে শেখার জার্নি! 

Live Class 1: SDLC Models and Where QA Fits

What SDLC is and its phases | Waterfall in brief: one worked example, pros and cons | V-Model and why test planning starts early | Agile Manifesto and principles | Scrum roles, sprint, ceremonies and artifacts; Kanban basics | QA in Agile: shift-left testing and Definition of Done | How AI changes each phase: more AI-written code means more code to test

Live Class 2: Requirements Analysis and Acceptance Criteria with AI

Reading requirements and user stories (INVEST) | Acceptance criteria in Given/When/Then (Gherkin basics) | Finding ambiguity, missing rules and contradictions | Prompting AI to review a user story, then accepting, modifying or rejecting each suggestion | Testability review of a requirement | Hands-on with a real user story

Live Class 3: STLC, Test Levels and Test Planning with AI

STLC vs SDLC; STLC phases with entry and exit criteria | Requirement Traceability Matrix (RTM) and static testing (reviews) | Test levels: unit, integration, system, acceptance | What a test plan contains: scope, approach, risks, schedule, entry and exit criteria | Introduction to risk-based testing and estimation | Drafting a test plan with AI, then critiquing what is generic, missing or wrong

Live Class 1: What is SQA and How AI Is Reshaping QA

What software quality means and why it matters, with real-world failure examples | QA vs QC vs Testing | Objectives of SQA and the 7 testing principles | Where AI helps (test generation, maintenance, analysis) and where it fails (hallucination, missing context, false confidence) | Live demo: an AI agent (Claude Code + Playwright MCP) explores a demo web app and reports issues | Debrief: which reported bugs were real and what the agent missed | The three pillars of AI Native QA: Test with AI, Verify AI, Test AI | Hands-on: break a public AI chatbot (wrong facts, made-up answers, broken format) and log what went wrong

Live Class 2: QA Roles, Career Paths and Your First Automated Test

QA roles in Bangladesh and remote markets: SQA Engineer, QA Automation Engineer, SDET, AI QA / LLM Evaluation Tester | Career ladder from junior tester to QA Lead and AI Test Engineer | A day in the life of a QA engineer using AI tools | Hands-on: install Playwright and record a test with codegen | Ask Claude Code to explain every line, then run the test and read the HTML report | Push the first test to GitHub

Live Class 1: Test Design Techniques I

Equivalence partitioning | Boundary value analysis | Decision tables | Practice on login, signup and payment amount fields

Live Class 2: Test Design Techniques II

State transition testing | Use-case testing | Pairwise testing | Error guessing | Intro to exploratory testing | AI generates cases with a named technique; learners find the gaps

Live Class 3: Writing and Reviewing Test Cases with AI

Anatomy of a test case: ID, preconditions, steps, data, expected result | Positive, negative and edge cases; checklists vs test cases | Prompting AI with a named technique (for example: apply BVA to this field) | Reviewing AI test cases: duplicates, missing boundaries, vague expected results | Coverage check against the RTM | Test case template in Excel or Google Sheets

Live Class 1: JavaScript Basics, Hand-Coded First

Why JavaScript for QA: Playwright, k6, Postman scripts and Promptfoo all use it | Variables (let, const), data types and operators | Conditions and loops; template literals | Write by hand first, then ask AI to explain or compare | Debugging with console.log and the VS Code debugger

Live Class 2: Functions, Arrays, Objects and JSON

Functions and arrow functions | Arrays and array methods (map, filter, find) | Objects and JSON | Reading and writing test data files | Hand-coded drills, then AI review

Live Class 3: Async JavaScript, Modules, Classes and Node.js

Promises and async/await, essential for Playwright | Modules (import, export), npm and package.json | Classes and objects (needed for Page Object Model) | Using Claude Code to refactor and explain code | Spotting wrong AI code

Live Class 1: Problem Solving with AI as Co-Pilot

Breaking problems into input, output, constraints and edge cases | Pseudocode and flowcharts | Prompt pattern: break, ask, refine, validate | QA-style problems: validate a Bangladeshi phone number or email, parse test data, compare two lists | Classes and objects basics (needed for Page Object Model)

Live Class 2: From AI Plan to Tested Code

Writing small functions with unit tests (Node test runner) | AI generates, human reviews and tests | Reading unfamiliar code, a daily QA skill | Common AI code mistakes: off-by-one, missing edge cases, invented APIs | When to accept, modify or reject AI code

Live Class 3: Git and GitHub Essentials

Why version control | init, add, commit, log, diff; .gitignore | GitHub repository, push, pull, README | Branches and merge | AI-written commit messages, checked by a human

Live Class 4: Team Workflow: Pull Requests and Code Review

Feature branch workflow | Pull requests, review comments and resolving conflicts | Reviewing test code in a PR | GitHub Copilot review and Claude Code PR summaries, verified by a human | GitHub Issues as a bug tracker | Portfolio repository structure