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1. Setting Up AI Agents

Get your tools ready for hands-on learning. This chapter walks you through installing Visual Studio Code, setting up GitHub Copilot, and configuring OpenCode — an open-source AI coding agent — so you can follow along and practice throughout the course. Watch now

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2. AI in API Testing

This chapter maps out the key areas where AI genuinely adds value in API testing — from exploratory testing and tool usage, to automated tests, one-off scripts, and test data generation — setting the stage for the hands-on work ahead. Watch now

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3. Setting Up Python

A quick but essential setup step. This chapter walks you through installing Python, running commands in the interpreter, and executing scripts from the terminal — just enough to keep up with the hands-on exercises ahead without needing any prior programming experience. Watch now

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4. Setting Up A Testing API

Meet the sample APIs you'll use throughout the course. This chapter covers how to access the hosted version for quick follow-along practice, and how to clone and run the project locally if you want to go deeper — no prior Git experience needed. Watch now

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5. Exploring With AI

See AI-assisted exploration in action. This chapter shows how to craft effective prompts to uncover undocumented endpoints, spot mismatches between API docs and actual behavior, and search a codebase for hidden routes — plus how to verify findings before raising them as bugs. Watch now

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6. Open API And AI

Discover how OpenAPI specs and AI are a natural fit. This chapter covers what an OpenAPI spec is, how to use AI to audit one for gaps and security issues, enrich it with real examples, and even generate one from scratch when your API doesn't have documentation yet. Watch now

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7. Building and Using API Collections with AI

API collections are a powerful, text-friendly format that works across multiple tools. This chapter shows how to generate a collection from an OpenAPI spec, use it to identify and build realistic workflow tests, and connect it to tools like Tricentis Tosca — including via an MCP server — all driven by AI prompts. Watch now

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8. API Tool Usage With AI

Step back and think strategically about combining AI with API tools. This chapter covers how to choose text-based tool formats that work well with AI, stay safe with credentials and delete operations, use curl as a quick AI-assisted entry point, and build your own reusable skills — rather than blindly trusting ones you download. Watch now

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9. Validating 3rd Party APIs

Testing APIs you don't own comes with unique challenges. This chapter covers how to use AI to debug cryptic error responses, set up mock servers to simulate unavailable third-party endpoints, and use Tricentis Tosca's service virtualization as a faster alternative — so you can test your full application workflow without depending on external services. Watch now

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10. What Makes A Good Test

AI-generated code changes the testing landscape in subtle but important ways. This chapter explores how AI introduces higher variance in code quality, why verifying that code solves the right problem matters more than ever, and what a great bug report looks like. Watch now

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11. End-to-End API Testing

End-to-end testing means more than just chaining requests together. This chapter explores the contextual challenges of full-stack testing — API gateways, rate limiters, load balancers — and shows how to use AI to simulate those conditions locally and hunt down tricky timing bugs like race conditions with AI-generated scripts. Watch now

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12. Tosca

A walkthrough of Tosca for API testing. This chapter shows how to import an OpenAPI spec to create a simulation, use an AI agent to interpret and fix errors on the fly, and get a working test suite running in minutes — even with no prior Tosca experience. Watch now

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13. Integration Testing with AI Assistance

You don't need to be a developer to contribute to integration testing. This chapter shows how to use an AI agent to run tests, interpret failures in plain English, fix outdated tests after API changes, and validate test quality through mutation testing — all without needing to deeply understand the underlying code. Watch now

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14. One Off Scripts

Some tests are worth running but too tedious to set up manually. This chapter shows how to use an AI agent to quickly generate throwaway scripts that automate complex test setups — turning a test you'd normally skip into a five-minute task that can surface surprising bugs in the process. Watch now

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15. Unit Tests

Unit testing doesn't have to be a developer-only activity. This chapter shows how to design your own test scenarios first — focusing on edge cases — before handing them to an AI to write, so you avoid the confirmation bias that comes from letting AI read the code and test what it already knows. Watch now

16. What Makes Good Test Data

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17. Data That Fits The Schema

Put your test data theory into practice. This chapter shows how to quickly generate realistic, schema-aligned test data, import it into Tosca for test validation, and even use it to drive a NeoLoad performance test — all set up with a few AI-assisted prompts, no manual configuration needed. Watch now

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18. Custom Test Data

Good testing means going beyond valid data. This chapter shows how to use AI to brainstorm and generate edge-case inputs — special characters, unusual names, malformed emails, and security payloads — then export them into a CSV and run them as a bulk test suite in Bruno to stress-test your API in minutes. Watch now

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19. Extracting Data From Your Site

The most realistic test data often comes from your own application. This chapter covers two approaches — pulling data via API calls and web scraping — to capture production-like data, transform it into a CSV, and use it to populate your local testing environment, all with a few AI-assisted prompts and without touching real PII. Watch now

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20. Conclusion

A look back at everything covered in the course — from API exploration and OpenAPI specs, to mock servers, unit and integration tests, one-off scripts, and test data generation. More importantly, a reminder to stay in the driver's seat: use AI as a powerful assistant that sharpens your testing, not one that replaces your thinking. Watch now

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16. What Makes Good Test Data

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