Written by the AgileFever editorial team. Program details were checked against the live program pages in October 2026. We teach this course. Prices come from our public catalog and were checked on October 29, 2026.
The honest answer depends on what you do today. This post gives a fit test, shows what the course covers and suggests a short exercise you can do before you pay.
A fit test
| If this describes you | Worth it? | Why |
|---|---|---|
| You write Selenium, Cypress or Playwright tests and lose time to broken locators and thin test plans | Likely yes | Two modules target test generation and self-healing scripts |
| You test products that now contain an LLM feature and have no way to evaluate its answers | Likely yes | The page covers golden datasets and evaluation with LLM-as-judge and human review |
| You are a manual tester who has never written code | Not yet | Python for AI is required first, and the page expects basic QA concepts such as test case design |
| You want to build and ship AI products | No | A bootcamp covers retrieval, agents and deployment in more depth |
| You lead QA and want a view without doing the labs | Maybe | Read the module list first. The labs are hands-on, so the course is for people who do the work |
What the course covers
Six modules. Three use generative AI: test plan and case generation, automation scripts with self-healing patterns, and bug report generation from logs, screenshots and reproduction steps. Three use agentic AI: agents for regression, performance and OWASP security checks, evaluation testing for LLM and agent outputs, and triage and quality reporting agents.
Assessment is a final test covering all six use cases plus hands-on labs in each module. A certificate of completion is issued on passing. Live sessions are recorded.
US dollars, and hours
Time: 12 live hours plus 6 hours for the prerequisite, about 18 hours in total.
Additional discounts are available. Contact us to know more.
What to try before you pay
Take one feature specification from your current sprint and ask any AI assistant for positive, negative and edge-case tests. Then compare the output with your own test cases. Count what it missed, what it got right and how long you spent correcting it. Ten minutes of that will tell you whether the first module is a gap for you. Do the same with a recent bug: paste the logs and see whether the report it drafts is one a developer could act on.
If the results excite you or frustrate you in a specific way, you have a reason to take the course. If you feel nothing either way, save the money.
Who should look elsewhere
- If you want to build AI systems, the GenAI and Agentic AI BootCamp is the program for that.
- If you are still learning to code, start with Python for AI.
The course page is Gen AI and Agentic AI for QA and Test Engineers. Related reading: the full cost breakdown, the skills you build, the QA to AI Test Engineer roadmap and the complete guide.
Questions people ask
Will AI replace QA engineers?
The course page says AI can automate parts of execution and repetitive work but does not replace test strategy, quality decisions, debugging and risk assessment. We cannot predict the job market, so treat that as the program’s position.
Do I need to know Selenium or Cypress?
The page expects comfort with basic QA concepts, such as test case design, Selenium or Cypress.
Can my employer pay?
Many employers reimburse training. Our post on pitching an AI upskilling budget shows how to build the case.
