Manual QA

- Why testing matters; the real cost of defects; QA vs. QC vs. Testing

- Software Development Life Cycle (SDLC) and Software Testing Life Cycle (STLC)

- Testing in Waterfall vs. Agile models

- Agile/Scrum fundamentals and the QA engineer's role inside a Scrum team

- JIRA and Confluence for test management and documentation

- Test plans, test strategy, and requirement traceability matrices

- Writing effective, maintainable test cases and test suites

- Equivalence Partitioning, Boundary Value Analysis, Decision Tables

- Exploratory testing as a structured discipline

- Test levels: Unit, Integration, System, Acceptance; functional vs. non-functional

- Smoke, sanity, and regression testing; Black/White/Grey Box; Alpha/Beta testing

- Bug lifecycle, severity vs. priority

- Writing bug reports developers actually want to read

AI Spotlight: Using AI to summarize logs and screenshots into a clear bug report, and to suggest severity/priority — with the tester always reviewing before submitting.

- Prompt engineering fundamentals for QA (the foundation reused in every later AI module)

- Generating test cases and scenarios from user stories with ChatGPT/Claude

- AI-assisted exploratory testing — prompting AI to suggest risk areas and edge cases

- Generating synthetic test data with AI

- Data privacy and compliance when using AI tools with sensitive (banking) data

Project Checkpoint: Manual QA Baseline: write a full manual test suite and bug report set against saucedemo.com, a real, live e-commerce demo application. This test suite becomes the reference spec that later automation phases will convert into code.

- REST and SOAP basics, HTTP methods, status codes

- Postman: collections, environments, variables

- Reading Swagger/OpenAPI specifications

Project Checkpoint: Write manual Postman test cases against two real, live public APIs — Swagger Petstore (petstore.swagger.io) and restful-booker — covering CRUD operations, auth, and negative scenarios.

- Postbot: generating assertions from plain-English prompts (no code required)

- Reviewing and correcting AI-generated test scripts before trusting them

- Relational database basics; writing SELECT, JOIN, and filter queries

- Backend data validation for API and UI tests

- Hands-on with MySQL

Project Checkpoint: API Test Suite v1: a Postman collection (with Postbot-assisted assertions) against Petstore and restful-booker, backed by SQL queries that confirm the API response matches the database. This collection is the seed for the Phase 5