Practical teaching
In addition to class hours, you will practice the topics covered with your instructor and mentor dur
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Learn the fundamentals of manual software testing including test case design, bug reporting, and test management processes. This course is perfect for beginners entering software quality assurance roles. Experienced trainers provide practical sessions using real-world examples.
In addition to class hours, you will practice the topics covered with your instructor and mentor dur
The knowledge and skills you learn at the academy will be further strengthened with the mentor syste
Assignments and projects are checked by the instructor, and your knowledge and skills are determined
Modules stay collapsed for quick scanning. Open any module to inspect its topics.
- 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
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Course delivery is supported by practitioners across engineering, architecture and production backend development.
“The program helped me connect individual skills into the way real teams design, build and deliver software.”
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SELECTED TRAININGManual Testing & AI-Assisted QAOn-site
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