Training catalog
Practical, hands-on courses on applying AI to software testing and QA — delivered as in-company training or open sessions for individuals.
AI in Testing
A comprehensive, hands-on introduction to using AI tools and concepts throughout the software testing lifecycle — from test design to execution to maintenance.
- Core AI concepts every tester should know
- Using AI to generate and review test cases
- AI-assisted exploratory testing
- Where AI helps, and where it doesn't (yet)
- Building a review process for AI-generated output
AI-Driven API Test and Automation
A hands-on workshop where you use an AI coding assistant to implement and test a REST API from scratch — writing functional tests with Mocha and Supertest, running performance tests with k6, and wiring it all into a CI pipeline with GitHub Actions.
- REST API architecture fundamentals
- Generating and refining an API with an AI coding assistant
- Functional test automation with Mocha + Supertest
- Load testing with k6
- Continuous integration with GitHub Actions
AI-Driven Web Test and Automation
The web counterpart to our API automation workshop — use an AI coding assistant to build and test a web application end-to-end, from UI test design to a working automated suite integrated into CI.
- AI-assisted UI test design
- Generating resilient, maintainable web automation with an AI coding assistant
- Choosing the right locators and waits
- Integrating web tests into a CI pipeline
Testing MCP Servers
As Model Context Protocol (MCP) servers become the way AI agents connect to real systems, someone has to test them. This training covers how to validate MCP servers for correctness, reliability, and safety.
- How MCP servers work and where they fit in an AI system
- Designing test cases for tool definitions and responses
- Testing for reliability under malformed or adversarial input
- Regression testing as MCP servers evolve
Testing Chatbots
Chatbots and conversational AI break in ways traditional software doesn't. This training builds a practical framework for testing conversational flows, edge cases, and AI response quality.
- What makes chatbot testing different from traditional QA
- Designing conversation-flow test cases
- Evaluating AI response quality and consistency
- Regression testing for prompt and model changes
Modern Software Testing
A refresh on what software testing looks like today — combining solid testing fundamentals with modern practices and AI-assisted workflows, for teams who want to raise their baseline.
- Current testing fundamentals and mindset
- Where AI fits into a modern testing strategy
- Balancing manual, automated, and AI-assisted testing
- Building a practical, sustainable QA process