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BeginnerProgramming

Python for QA Engineers

Build clear Python foundations through realistic e-commerce QA examples, browser exercises, data workflows, and an order-audit capstone.

Python fundamentalsTest dataJSON and CSVDebuggingQA utilities
Learning outcomes

What you’ll be able to do.

01

Write readable Python for focused QA tasks

02

Create and transform representative test data

03

Inspect JSON and CSV evidence safely

04

Build reusable validation utilities

05

Debug failures and report limitations

Curriculum

8 focused modules.

32 lessons total
01Why Python matters and what this course will teach youUnderstand why Python matters in QA work. Preview the knowledge, practical skills, and outcomes that you will build.
  1. ↳Welcome to Python for QA EngineersLesson
  2. ↳What programming is and how Python runsLesson
  3. ↳Use the browser Python lab safelyLesson
  4. ↳Read, run, and debug your first QA scriptLesson
02Values and expressionsRepresent product facts with clear Python values and expressions.
  1. ↳Names, types, and valuesLesson
  2. ↳Strings, formatting, and normalizationLesson
  3. ↳Numbers, Boolean values, and comparisonsLesson
  4. ↳Build a checkout-state classifierLesson
03Decisions and repetitionTurn product rules into readable branches and controlled iteration.
  1. ↳Make decisions with conditional rulesLesson
  2. ↳Inspect evidence with loopsLesson
  3. ↳Use ranges, enumeration, and comprehensionsLesson
  4. ↳Create a boundary-value generatorLesson
04Collections for test dataChoose collection types that preserve the meaning of QA evidence.
  1. ↳Use lists and tuples for ordered evidenceLesson
  2. ↳Model records with dictionariesLesson
  3. ↳Use sets for uniqueness and coverageLesson
  4. ↳Build a reusable test-data matrixLesson
05Functions and modulesCreate small Python units that other QA work can reuse.
  1. ↳Design function inputs and outputsLesson
  2. ↳Decompose work and add type hintsLesson
  3. ↳Use standard-library modulesLesson
  4. ↳Build a test-data factoryLesson
06QA data workflowsRead, transform, compare, and report common test-data formats.
  1. ↳Read JSON API evidenceLesson
  2. ↳Process CSV test dataLesson
  3. ↳Use temporary files and context managersLesson
  4. ↳Compare expected and actual datasetsLesson
07Reliable professional utilitiesMake QA scripts diagnosable, maintainable, and safe for team use.
  1. ↳Handle exceptions and invalid inputLesson
  2. ↳Debug failures and produce useful logsLesson
  3. ↳Model QA records with data classesLesson
  4. ↳Create reviewable QA utilitiesLesson
08Course synthesisCombine Python foundations into one evidence-producing QA workflow.
  1. ↳Plan the order-audit capstoneLesson
  2. ↳Build the order-audit utilityLesson
  3. ↳Harden the utility and report evidenceLesson
  4. ↳Review outcomes and choose next stepsLesson
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