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Modern QA: Python, NumPy, and Data for Test Engineers

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About Course

Welcome to Software Testing with Python, NumPy, and Data — a hands-on learning experience designed to bridge the gap between traditional QA and modern data-driven testing. In this course, you’ll start by mastering the fundamentals of software testing, learning how real-world projects are built, tested, and delivered. As we move forward, you’ll dive into Python — the language powering today’s most advanced testing and analytics tools. You’ll learn to automate test cases, handle data efficiently, and make sense of results using NumPy and other data-handling techniques.

Whether you’re new to QA or upgrading your skills for today’s AI-driven world, this course will help you gain the confidence to think like a tester, code like an engineer, and analyze like a data scientist.

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What Will You Learn?

  • Manual Testing Foundations
  • Python Programming Language
  • Web Application Testing with Playwright
  • API Testing with Pytest
  • Data Handling with Pandas
  • AI Agents and Prompt Engineering
  • LangChain and OpenAI API

Course Content

Discord Channel Link
https://discord.gg/v9ees4bWDF

  • DIscord Link

Manual QA Concepts
This module introduces the fundamentals of software testing and the QA mindset. You’ll understand how software problems are identified, documented, and prevented through structured processes. Topics include SDLC, STLC, defect lifecycle, test case design, and real-world examples of requirement analysis and test planning. By the end, you’ll have a clear picture of how QA ensures software quality before automation begins.

Database and SQL and REST API
Modern applications rely on databases, and testers must validate what happens behind the scenes. In this module, you’ll learn the essentials of relational databases and SQL — writing queries to retrieve, update, and verify data. You’ll practice joining tables, checking data integrity, and validating backend logic to ensure complete end-to-end testing confidence.

Data Validation for Migration (On-Prem to Cloud)
Data migration testing is critical when companies move from traditional on-premise servers to modern cloud environments. This module focuses on validating data accuracy, completeness, and consistency between systems. You’ll learn how QA testers plan, execute, and report on data validation activities — using SQL and manual comparison methods — ensuring no data is lost or corrupted during migration.

Interview Prep for Manual (2 days – Optional)

Basic of Python Programming Language

Advance of python Programming Language (OOP)

Test Framework with Begave BDD

Python with NumPy and Pandas

Build & Use a Custom AI Model for QA

Prepare and Train Your Own Model

Apply the Model to Testing

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