Live Course
💎 11500
Part of AI Career Accelerator Path
[April 2025] How to Test AI Apps: The Most In-Demand QA Skill
Master AI Testing & Land a $300K+ Job
The most hands-on AI testing course is designed to make you job-ready. Learn how to test AI models like a pro and position yourself for top-tier AI QA roles.
Duration: 8 lectures (16 hours)
Instructors: Igor Dorovskikh, Vladimir Tanev
Free support in Discord included in the course price
😭 Sorry, the course is over
But soon the course will be available again.
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Key course features
AI testing is different—standard methods don’t work. This course gives you hands-on experience with real AI applications, using industry tools like Langtest, Promptfoo, LMStudio, and ChatGPT.
What you’ll do:
- Set up and run tests on AI models from the start
- Find and fix AI failures using real debugging techniques
- Assess LLMs for accuracy, bias, and security risks
- Work with open-source tools for AI testing
- Complete hands-on projects and prepare for AI testing roles
Why you should sign up
The QA field is changing rapidly due to AI, which threatens our jobs as QA. If you are a QA who fears being replaced by AI and wants to stay competitive in 2025, this course is for you.
If you want to land a $300K+ high-paying job offer in the next 4 months, you should sign up for this course.
⚠️ Course requirements
AI testing is different—standard methods don’t work. This course gives you hands-on experience with real AI applications, using industry tools like Langtest, Promptfoo, LMStudio, and ChatGPT.
What you’ll do:
- Set up and run tests on AI models from the start
- Find and fix AI failures using real debugging techniques
- Assess LLMs for accuracy, bias, and security risks
- Work with open-source tools for AI testing
- Complete hands-on projects and prepare for AI testing roles
Course syllabus
Vladimir Tanev, Igor Dorovskikh
- Learn AI app architecture and key components.
- Understand why AI testing differs from standard app testing.
- Set up your testing environment (Python, Node.js, LMStudio, API keys).
- Tools: LMStudio, ChatGPT, Grok 3, Anthropic.
- Activities: Lecture on AI basics, hands-on setup, and running simple queries.
Igor Dorovskikh, Vladimir Tanev
- Introduction to Promptfoo for LLM testing and red teaming.
- Tools: Promptfoo.
- Activities: Lecture on Promptfoo, setup, and hands-on prompt testing.
Igor Dorovskikh, Vladimir Tanev
- Apply Promptfoo to test LLMs in real AI applications.
- Debug test results for model improvements.
- Tools: Promptfoo, Real AI Application, LMStudio.
- Activities: Hands-on LLM testing and debugging.
Vladimir Tanev, Igor Dorovskikh
- Introduction to Qase.io for test case management.
- Choose a bug tracking tool (e.g., Notion).
- Debug AI failures based on test results.
- Tools: Langtest, Real AI Application.
- Activities: Lecture on debugging, hands-on fixing identified issues.
Igor Dorovskikh, Vladimir Tanev
- Introduction to testing AI models for accuracy and bias.
- Learn why Langtest is essential for AI testing.
- Tools: Langtest, LMStudio.
- Activities: Lecture on AI testing, Langtest setup, hands-on testing with a pre-trained model.
Vladimir Tanev, Igor Dorovskikh
- Apply Langtest to real AI applications.
- Conduct tests, analyze results, and present findings.
- Tools: Langtest, LMStudio, Real AI Application.
- Activities: Hands-on testing and result analysis.
Igor Dorovskikh, Vladimir Tanev
- Deep dive into Langtest and Promptfoo.
- Explore and integrate other open-source AI testing tools.
- Tools: Langtest, Promptfoo, ChatGPT, Grok 3, Anthropic, LMStudio, Real AI Application.
- Activities: Hands-on tool integration into workflows.
Vladimir Tanev, Igor Dorovskikh
- Review course content and discuss the future of AI testing.
- Tools: None specific.
- Activities: Wrap-up session and Q&A.
- How to position yourself in the job market with AI skills
Vladimir Tanev, Igor Dorovskikh
- Resume building and interview preparation.
- Learn how to highlight AI testing skills in job applications.
- Activities: Resume review, mock interviews, and career tips.
Engenious University reserves the right to change the modules' order to ensure the most efficient education process. All live lectures will be recorded and share with you thereafter. The course will include a mix of lectures, interactive discussions, hands-on exercises, and team activities to ensure active participation and practical learning experience for the students. Each week's content will be covered over two days, with time allocated for exercises and discussions.
Description
AI is rapidly transforming software development, and QA professionals need the right skills to keep up. This course provides a comprehensive, hands-on approach to testing AI systems, covering everything from data validation to model evaluation and AI-powered test automation. You will learn key AI testing challenges, how to assess AI models, and how to integrate AI testing into real-world workflows. The course includes practical exercises using open-source tools like LMStudio, Hugging Face, Selenium, and more.
Over four weeks, we will explore end-to-end AI testing strategies, including testing AI data pipelines, validating machine learning models, and monitoring AI systems after deployment. You will also discover how AI can assist in testing by generating test cases, automating defect management, and optimizing test execution. Each session includes live instruction, recorded lessons, hands-on homework assignments, and weekly homework reviews to ensure deep learning.
By the end of this course, you will have the confidence and expertise to test AI-driven applications, future-proof your QA career, and stay ahead in the AI-powered tech industry.
⚠️ Course requirements
AI testing is different—standard methods don’t work. This course gives you hands-on experience with real AI applications, using industry tools like Langtest, Promptfoo, LMStudio, and ChatGPT.
What you’ll do:
- Set up and run tests on AI models from the start
- Find and fix AI failures using real debugging techniques
- Assess LLMs for accuracy, bias, and security risks
- Work with open-source tools for AI testing
- Complete hands-on projects and prepare for AI testing roles
Who this course is for:
- QAs who fear being replaced and want to future-proof their careers.
- Manual QAs who need AI skills to stay competitive in 2025.
- Software testers looking for high-paying AI roles.
- Tech professionals curious about AI testing and automation.
Instructors
CEO and Founder
Igor is an accomplished CEO and Founder of Engenious.io, with 15+ years of experience in software testing and development and over a decade in management. He has worked at Barnes & Noble, Expedia, Tinder, and consulted at Apple and Grammarly. In the mentorship program, Igor offers expertise in building a testing process from scratch, leadership success, understanding C-level executives' expectations, selecting the right technology stack, providing and collecting feedback, and team growth. Mentees benefit from Igor's insights on creating efficient testing processes, fostering productive teams, aligning with executive priorities, making informed technology choices, establishing feedback channels, and securing resources for team development. With Igor as their mentor, participants gain valuable knowledge, skills, and perspectives to excel as Dev/QA Directors or Managers.
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Senior iOS Engineer to Co-Founder & CTO·WeOptimize.ai
Vladimir is an experienced engineer with 8+ years in iOS/macOS development, specializing in AI-powered solutions. As the Co-Founder & CTO of WeOptimize.ai, he leverages AI to optimize workflows and enhance productivity. He has a track record of delivering innovative products for both startups and large enterprises.
FAQ
Yes, all live sessions will be recorded and made available to participants for review.
Live sessions will be held on Saturday or Sunday mornings (U.S. time):
- PST: 9:00 AM – 11:00 AM
- EST: 12:00 PM – 2:00 PM
- CET: 6:00 PM – 8:00 PM
All course materials, including recordings, slides, and additional resources, will be available on the course platform, which you will gain access to upon enrollment.
The course runs for 4 weeks, with weekly live sessions of 2 hours each, plus practical homework assignments.
You can sign up directly through the course registration page. Once you register, you’ll receive further instructions on accessing the course materials and joining the live sessions.
Absolutely! After each live session, you’ll receive homework assignments, which you can submit for feedback. The instructor will review and provide feedback on your homework to ensure you're progressing and grasping the concepts.
Yes, you’ll have access to a Discord community where you can ask questions, share experiences, and collaborate with fellow students. There will also be opportunities for interaction during the live sessions.
The course spans 4 weeks, with live sessions that are 2 hours long each, held on weekends. In addition to the live sessions, you’ll need to spend time each week completing hands-on homework assignments, which typically take around 2-4 hours.
No prior AI experience is required! This course starts with the basics and gradually builds your knowledge of AI testing concepts and tools. However, a basic understanding of software testing and some familiarity with programming (Python recommended but not required) will help you get the most out of the course.