Certified Associate Tester with Python (PCAT) Online Training

Software teams that lack a shared testing approach can ship regressions, slow releases, and rely too heavily on a few experienced reviewers. This intermediate PCAT™ training gives IT Directors and Team Leads a structured path for bringing QA engineers, aspiring testers, and Python developers onto common practices for Python test automation.

The course is a realistic assignment of about 26 hours per learner before practice time. It fits teams standardizing on Python testing with unittest, PyTest, assertions, fixtures, parameterization, test doubles, mocking, TDD, BDD, interface testing, web interface testing, and refactoring. For regulated or change-controlled environments, this is not a compliance course, but it can support lower release risk by helping teams write more repeatable tests and adopt clearer quality practices.

For rollout, Training Managers can group the content into role-based Playlists and use Team Reporting to monitor completion and adoption.

IT teams complete this training to make Python testing less ad hoc and more repeatable across development and QA workflows. The curriculum maps to practical release-quality scenarios teams face when maintaining Python applications.

• Reduce regression risk: Teams learn to use assertions, fixtures, unittest, and PyTest to validate expected behavior before code reaches production.
• Improve test coverage without duplicating effort: Parameterized testing helps practitioners run the same logic across multiple inputs and edge cases.
• Isolate failures faster: Test doubles, mocking, advanced mocking, and monkeypatching help teams test components without depending on live services or hard-to-control dependencies.
• Support cleaner delivery practices: TDD, BDD, interface testing, web interface testing, and refactoring principles help teams connect quality practices to feature delivery and maintainable code.

Knowledge

• Software testing fundamentals, including levels of testing and core testing principles
• How Python assertions support automated validation
• xUnit architecture and the role of the unittest module
• PyTest basics, fixtures, parameterization, and monkeypatching concepts
• Test doubles, mocks, and when to isolate dependencies in tests
• TDD, BDD, property-based testing, interface testing, web interface testing, and refactoring principles

Ability

• Write Python tests with unittest and PyTest
• Apply assertion methods and fixtures to create repeatable test cases
• Use parameterized tests to cover multiple scenarios efficiently
• Replace external dependencies with test doubles, mocks, and monkeypatching where appropriate
• Structure unit tests around F.I.R.S.T. principles and method-testing strategies
• Apply TDD, BDD, interface testing, and refactoring practices to improve software quality