Break Into AI Testing: 5-weeks AI Career Accelerator

Live • Online • Zoom

AI & LLM TESTING BOOTCAMP

AI & LLM TESTING BOOTCAMP

AI & LLM TESTING BOOTCAMP

BREAK INTO AI TESTING

BREAK INTO AI TESTING

BREAK INTO AI TESTING

Live • Online • Zoom

Become an AI & LLM Testing expert in 5 weeks. The only hands-on, project-based AI testing training in the world — go from manual QA to next-gen AI QA and future-proof your career.

Become an AI & LLM Testing expert in 5 weeks. The only hands-on, project-based AI testing training in the world — go from manual QA to next-gen AI QA and future-proof your career.

Join our 5-month, part-time QA Bootcamp and gain the skills — including AI testing tools — for remote-friendly roles with a $63,250 median starting salary.

Apply for April Cohort

Request a Consultation

Customer
Customer
Customer
From 2000+ ratings

ENROLL BY

April 18

Limited spots available for the upcoming cohort

DURATION

5 Weeks Long

40 Live Hours + 80 hrs hands-on exercises

PREREQUISITES

For QAs with 1+ years of experience

Who want to move into AI-focused roles

The Skill That Changes Everything

The Skill That Changes Everything

QA engineers without AI skills

at risk of replacement

at risk of replacement

QA engineers with AI skills

among the most hired in tech

among the most hired in tech

Get job-ready fast

Get noticed

Build a portfolio

Find your edge

Be Fully AI Job-Ready by Graduation

Career readiness isn't an afterthought — it's part of the program. You'll get dedicated coaching, a strategy to grow your LinkedIn presence, and real project experience you can speak to in any interview.

We'll help you build your AI QA job search assets

LinkedIn

Portfolio

Get mentorship, job opportunities and peer support throughout Discord community, plus a network that stays with you.

Job leads

Community

Igor Dorovskikh

Management (CEO)

17 years of experience

Be Fully AI Job-Ready by Graduation

Career readiness isn't an afterthought — it's part of the program. You'll get dedicated coaching, a strategy to grow your LinkedIn presence, and real project experience you can speak to in any interview.

We'll help you build your AI QA job search assets

LinkedIn

Portfolio

Get mentorship, job opportunities and peer support throughout Discord community, plus a network that stays with you.

Job leads

Community

Igor Dorovskikh

Management (CEO)

17 years of experience

Get directly connected to recruiters

250+

companies in the employer network

You're not alone in your job search. We are actively expanding our employer network, and will send your resume directly to companies when open roles match your skills.

>90%

of students who complete online externships get hired

How do you find a job when everything requires experience? Here’s how: you’ll have opportunities to work on short, real-life projects for partner companies.

Get real experience through TripleTen externships

Graduate with a portfolio of fresh, relevant projects

The projects you’ll work on during your studies are based on current employer needs in 2026. Choose the projects that reflect your personal talents and interests.

Your portfolio will demonstrate:

Real-world experience

Your unique viewpoint

Collaboration skills

AI tool mastery

You’re shifting careers, not starting from scratch.

Your past experiences mean something. During career coaching, we’ll show you how to weave your work history, strengths, and passions into a story that makes employers take notice.

Mavis Herring

Mavis became an AI QA Engineer

Mavis was a QA engineer looking to stay ahead of where the industry was heading. After completing the program, she gained hands-on AI testing skills that directly strengthened her profile and helped her land her next role.

Be Fully AI Job-Ready by Graduation

Career readiness isn't an afterthought — it's part of the program. You'll get dedicated coaching, a strategy to grow your LinkedIn presence, and real project experience you can speak to in any interview.

We'll help you build your AI QA job search assets

LinkedIn

Portfolio

Get mentorship, job opportunities and peer support throughout Discord community, plus a network that stays with you.

Job leads

Community

Igor Dorovskikh

Management (CEO)

17 years of experience

Get directly connected to recruiters

250+

companies in the employer network

You're not alone in your job search. We are actively expanding our employer network, and will send your resume directly to companies when open roles match your skills.

>90%

of students who complete online externships get hired

How do you find a job when everything requires experience? Here’s how: you’ll have opportunities to work on short, real-life projects for partner companies.

Get real experience through TripleTen externships

Graduate with a portfolio of fresh, relevant projects

The projects you’ll work on during your studies are based on current employer needs in 2026. Choose the projects that reflect your personal talents and interests.

Your portfolio will demonstrate:

Real-world experience

Your unique viewpoint

Collaboration skills

AI tool mastery

You’re shifting careers, not starting from scratch.

Your past experiences mean something. During career coaching, we’ll show you how to weave your work history, strengths, and passions into a story that makes employers take notice.

Mavis Herring

Mavis became an AI QA Engineer

Mavis was a QA engineer looking to stay ahead of where the industry was heading. After completing the program, she gained hands-on AI testing skills that directly strengthened her profile and helped her land her next role.

Upfront

Get the best price when you pay once.

See All Upfront Prices

Installment

Split tuition into smaller payments with Klarna.

See Installment Options

Refund

Full refund - no questions asked.

Learn More

You After The Bootcamp

You After The Bootcamp

AI Test Engineer

Portfolio-ready AI and LLM testing experience built on a real U.S. startup project with live, hands-on training.

$180,000

Expected salary

Skills

LLM evaluation

LLM evaluation

Hallucination + factual drift detection

Hallucination + factual drift detection

LLM-graded assertions

LLM-graded assertions

Prompt injection + jailbreak testing (red teaming)

Prompt injection + jailbreak testing (red teaming)

Multi-model comparison

Multi-model comparison

Bug reports for AI failures

Bug reports for AI failures

Tools

Promptfoo

LM Studio

Agenta

Arato.ai

OpenAI API

Anthropic API

PROOF OF WORK

Break Into AI Testing: The Next-Gen Quality Engineer Skillset

EnGenious University

Portfolio

ML for Mining: Gold Recovery Prediction

40+ hours of coding in Python, using industry-standard ML libraries.

AI Application Testing

AI Application Testing Portfolio

AI Application Testing Portfolio

Hands-on artifacts covering LLM evaluation, prompt injection and jailbreak testing, multi-model comparison, and hallucination detection — built using Promptfoo, OpenAI API, Anthropic API, and LM Studio.

Our Alumni Work at

Our Alumni Work at

Will I get a certificate?
Of course! It’ll look great on your resume and LinkedIn

Will I get a certificate?
Of course! It’ll look great on your resume and LinkedIn

Will I get a certificate?
Of course! It’ll look great on your resume and LinkedIn

Will I get a certificate?
Of course! It’ll look great on your resume and LinkedIn

"After 5 years in manual QA, I landed an SDET role in just 2 months thanks to the AI Tester Accelerator"

Anastasiya Kliushkina

Android Jr. Engineer at Google

"After 5 years in manual QA, I landed an SDET role in just 2 months thanks to the AI Tester Accelerator"

Anastasiya Kliushkina

Android Jr. Engineer at Google

"After 5 years in manual QA, I landed an SDET role in just 2 months thanks to the AI Tester Accelerator"

Anastasiya Kliushkina

Android Jr. Engineer at Google

"The real-world focus of this program gave me genuine confidence in AI testing, and it's an absolute game-changer compared to anything else out there for QA engineers."

"The real-world focus of this program gave me genuine confidence in AI testing, and it's an absolute game-changer compared to anything else out there for QA engineers."

80% of our students landed new jobs or got promoted within 5-6 weeks after the training!

  • "I’d absolutely recommend it"

    Hershal Walton

    Product Manager

  • "I left buzzing with so many ideas"

    Max Volvich

    QA Leader

  • "I’d absolutely recommend it"

    Hershal Walton

    Product Manager

  • "I left buzzing with so many ideas"

    Max Volvich

    QA Leader

"I’d absolutely recommend it"

Hershal Walton

Product Manager, TIAA

"I left buzzing with so many ideas"

Max Volvich

QA Manager

"From QA to AI Testing"

Mavis Herring

AI QA Manager

Requirements

Why learning AI & LLM Testing is a must for Every QA in 2025?

Requirements

Our members are at the heart of everything we do. Hear their stories and find out why our community is unlike any other.

  • I was nervous to join a gym. But from the moment I walked into Energize, the trainers made me feel welcome and supported.

    ER

    Emily Rogers

  • I was nervous to join a gym. But from the moment I walked into Energize, the trainers made me feel welcome and supported.

    MD

    Michael Davis

  • I was nervous to join a gym. But from the moment I walked into Energize, the trainers made me feel welcome and supported.

    LM

    Laura Matthews

  • I was nervous to join a gym. But from the moment I walked into Energize, the trainers made me feel welcome and supported.

    SJ

    Sarah Johnson

  • I was nervous to join a gym. But from the moment I walked into Energize, the trainers made me feel welcome and supported.

    DL

    David Lee

  • I was nervous to join a gym. But from the moment I walked into Energize, the trainers made me feel welcome and supported.

    JB

    Jessica Brown

What Makes This Program Truly Different from Other Online Programs

Real startup project

You’ll test a real US-based AI startup app and graduate with a portfolio project you can add to your resume.

95% hands-on, live training

40 live hours + 80 hours of hands-on work. Minimal theory - mostly doing, feedback, and iteration.

Career positioning built in

Week 5 focuses on positioning: resume bullets, LinkedIn keywords, and interview storytelling - so your new skills show up in searches and callbacks

Recorded + reusable for a full year

All live sessions are recorded and available for up to 1 year, so you can revisit when you apply the work on the job

Is this program for you?

Is this program for you?

QA Engineers and SDETs who want to stay relevant as AI reshapes software testing

You're a manual QA with 3+ years of experience.

Automation Engineers looking to expand beyond traditional frameworks into AI system testing

You're a manual QA with 3+ years of experience.

Test Leads and QA Managers responsible for quality, risk, and governance in AI-powered products

You're a manual QA with 3+ years of experience.

Product Managers working on AI features who need to understand AI behavior, reliability, and risk

You're a manual QA with 3+ years of experience.

Software Engineers exploring AI-adjacent roles such as prompt engineering or AI quality

You're a manual QA with 3+ years of experience.

Requirements

Why learning AI & LLM Testing is a must for Every QA in 2025?

You must have 1+ year of manual QA experience

No coding or programming experience needed

Laptop with minimum specifications

See Requirements

Laptop with minimum specifications

See Requirements

Why learning AI & LLM Testing is a must for Every QA in 2026?


Why learning AI & LLM Testing is a must for Every QA in 2026?


Demand for AI Skills in QA have tripled in past years

More than 3,000+ job openings across the US

Top AI QAs earn over $300K/year

AI Testing Skills are in-demand in every company

Almost every company is building their AI products

 Ready to Begin Your AI Testing Journey?

 Ready to Begin Your AI Testing Journey?


The future of QA isn't about choosing between Selenium or Playwright - it's about Mastering Prompt Engineering, LLM Testing and AI Debugging.

The future of QA isn't about choosing between Selenium or Playwright - it's about Mastering Prompt Engineering, LLM Testing and AI Debugging.

The future of QA isn't about choosing between Selenium or Playwright - it's about Mastering Prompt Engineering, LLM Testing and AI Debugging.


The future of QA isn't about choosing between Selenium or Playwright - it's about Mastering Prompt Engineering, LLM Testing and AI Debugging.

Apply for April cohort

100% Money-Back Guarantee

100% money-back guarantee

Not sure if this course is right for you?

Not sure if this course is right for you?

Book a free AI Career Strategy Call and get personalized guidance before you enroll

Book a free AI Career Strategy Call and get personalized guidance before you enroll

Request a Consultation

AI Skills in QA have tripled in past years

Top AI QAs earn over $300K/ year

More than 3000+ job openings for AI testers across the US

AI Testing Skills are in-demand in every company

Almost every company is building their AI products

What you'll achieve in 5-weeks

Week 1 (Foundations and Tool Mastery)

Day 1: AI Fundamentals & Setup

Introduction: Course rules, setting up the permanent Discord community channel. Theory: LLM basics, transformer architecture, differences between traditional software testing and AI system testing. Hands-on: Environment setup (local and cloud models). Initial interactive model exploration comparing local (LM Studio) and commercial (OpenAI, Anthropic) models using the same prompt. Vulnerabilities: Introduction to the seven unique AI testing challenges (e.g., security, hallucination, bias). Homework: Complete environment setup and design 3+ test prompts targeting the vulnerabilities.

Day 2: PromptFoo Basics

Tool Introduction: Learning PromptFoo for systematic AI testing. Shift to hands-on, Q&A, and group exercises (minimal presentations). Configuration: Overview of PromptFoo's configuration (YAML structure), including providers (LLMs), prompts, and initial deterministic assertions (pass/fail checks). Practice utilizing variables within prompts. Integration: Testing commercial and local models via PromptFoo. Homework: Practice building test suites and reviewing assertions documentation.

Week 2 (Foundations and Tool Mastery)

Day 3: Prompt Engineering and Cost Evaluation

Prompt Engineering: Defining the rules and constraints of the system (System Prompt) and crafting effective test inputs (User Prompt). Using AI (LLMs) to generate effective test prompts. Evaluation: Hands-on workshop on LLM cost evaluation (budgeting) by running prompts against multiple models to compare cost per request. Organization: Structuring the testing framework using file-based prompt configurations.

Day 4: Advanced Assertion & Career Prep

Advanced Testing: Deep dive into assertions, particularly Model-Graded Assertions (MGA), where an LLM acts as a judge (LLM Rubric) to evaluate output quality (relevancy, factuality). Testing using CSV-based files for structured test data. Career Start: Introduction to LinkedIn Personal Branding; documenting early achievements and incorporating AI testing keywords (e.g., prompt engineering, LLM testing) to profiles. Homework: Review PromptFoo Red Teaming documentation.

Week 3 (Application Testing and Advanced Techniques)

Day 5: Red Teaming Concepts

Equator Point: Course halfway review. Red Teaming: Defining red teaming as simulating adversarial inputs (like a comprehensive baseline report) to find vulnerabilities (e.g., security, bias). Discussion of vulnerability frameworks like the OWASP Top 10 for AI. Strategy: Understanding Red Teaming workflow (defining strategy, execution, analysis) and configurations. Comparison of red teaming types (Small, Large, XXL/Extensive).

Day 6: Testing a Real Application (Red Team Web App)

Application Architecture: Reviewing the high-level architecture of the application (Orchestrator, Guard LLM, specialized LLMs, knowledge bases like Jira/Confluence/Figma). Testing Mode: Focusing on end-to-end black box exploratory testing via the application's chat interface. Using the provided "Source of Truth" as acceptance criteria. Bug Reporting: Hands-on exercise reporting and documenting bugs in ClickUp, including reproduction steps and linking them to specific AI vulnerabilities.

Week 4 (Application Testing and Advanced Techniques)

Day 7: Red Teaming Execution & Triage

Application Setup: Finalizing the Red Teaming configuration by inputting a comprehensive application context (main purpose, features, system rules) into PromptFoo. Group Triage: Teams exchange reported bugs and attempt to reproduce and validate issues found by classmates. Advanced Testing: Hands-on session applying PromptFoo for complex scenarios, including multi-turn conversation testing using JSON objects for regression. Tool Exposure: Alternative testing tool.

Day 8: Tool Exploration & Post-Launch Monitoring

Post-Launch Tools: Demo and discussion of tools used for monitoring and maintaining LLM models pre- and post-launch (e.g., Arato wrapper). New Tool Assignment: Introduction to Agenta (a comparable, alternative LLM testing platform). Homework: Explore and evaluate Agenta to apply foundational testing concepts learned from PromptFoo. Research other AI testing tools in the market (consulting mindset).

Week 5 (Career Acceleration)

Day 9: Agenta Review & LinkedIn Strategy

Tool Comparison: Reviewing homework findings on Agenta, applying foundational concepts (Evals, variables) learned from PromptFoo to a new platform. Career Branding: Strategies for content creation and influence building on LinkedIn. Using generative AI tools (e.g., Claude, ChatGPT) as brainstorming partners for posts, while avoiding generic copy-paste content. Accomplishments: Workshop focused on drafting AI LLM testing accomplishment statements for resumes/profiles, quantifying the business impact of skills learned. Homework: Post tailored AI testing content on LinkedIn and engage (comment/repost) with classmates' posts.

Day 10: Final Optimization & Interview Prep

Final Profile Optimization: Updating LinkedIn profiles and resumes with core AI testing skills (prompt engineering, red teaming, hallucination detection, token consumption). Interview Preparation: Review of common AI testing interview questions (e.g., scaling tests, verifying factual responses, token consumption, security, testing LLMs with other LLMs). Wrap-up: Final remarks, community engagement commitment, and discussion of post-course resources.

Apply for April Cohort

100% Money-Back Guarantee

What you'll achieve in 5-weeks

Week 1 (Foundations and Tool Mastery)

Day 1: AI Fundamentals & Setup

Introduction: Course rules, setting up the permanent Discord community channel. Theory: LLM basics, transformer architecture, differences between traditional software testing and AI system testing. Hands-on: Environment setup (local and cloud models). Initial interactive model exploration comparing local (LM Studio) and commercial (OpenAI, Anthropic) models using the same prompt. Vulnerabilities: Introduction to the seven unique AI testing challenges (e.g., security, hallucination, bias). Homework: Complete environment setup and design 3+ test prompts targeting the vulnerabilities.

Day 2: PromptFoo Basics

Tool Introduction: Learning PromptFoo for systematic AI testing. Shift to hands-on, Q&A, and group exercises (minimal presentations). Configuration: Overview of PromptFoo's configuration (YAML structure), including providers (LLMs), prompts, and initial deterministic assertions (pass/fail checks). Practice utilizing variables within prompts. Integration: Testing commercial and local models via PromptFoo. Homework: Practice building test suites and reviewing assertions documentation.

Week 2 (Foundations and Tool Mastery)

Day 3: Prompt Engineering and Cost Evaluation

Prompt Engineering: Defining the rules and constraints of the system (System Prompt) and crafting effective test inputs (User Prompt). Using AI (LLMs) to generate effective test prompts. Evaluation: Hands-on workshop on LLM cost evaluation (budgeting) by running prompts against multiple models to compare cost per request. Organization: Structuring the testing framework using file-based prompt configurations.

Day 4: Advanced Assertion & Career Prep

Advanced Testing: Deep dive into assertions, particularly Model-Graded Assertions (MGA), where an LLM acts as a judge (LLM Rubric) to evaluate output quality (relevancy, factuality). Testing using CSV-based files for structured test data. Career Start: Introduction to LinkedIn Personal Branding; documenting early achievements and incorporating AI testing keywords (e.g., prompt engineering, LLM testing) to profiles. Homework: Review PromptFoo Red Teaming documentation.

Week 3 (Application Testing and Advanced Techniques)

Day 5: Red Teaming Concepts

Equator Point: Course halfway review. Red Teaming: Defining red teaming as simulating adversarial inputs (like a comprehensive baseline report) to find vulnerabilities (e.g., security, bias). Discussion of vulnerability frameworks like the OWASP Top 10 for AI. Strategy: Understanding Red Teaming workflow (defining strategy, execution, analysis) and configurations. Comparison of red teaming types (Small, Large, XXL/Extensive).

Day 6: Testing a Real Application (Red Team Web App)

Application Architecture: Reviewing the high-level architecture of the application (Orchestrator, Guard LLM, specialized LLMs, knowledge bases like Jira/Confluence/Figma). Testing Mode: Focusing on end-to-end black box exploratory testing via the application's chat interface. Using the provided "Source of Truth" as acceptance criteria. Bug Reporting: Hands-on exercise reporting and documenting bugs in ClickUp, including reproduction steps and linking them to specific AI vulnerabilities.

Week 4 (Application Testing and Advanced Techniques)

Day 7: Red Teaming Execution & Triage

Application Setup: Finalizing the Red Teaming configuration by inputting a comprehensive application context (main purpose, features, system rules) into PromptFoo. Group Triage: Teams exchange reported bugs and attempt to reproduce and validate issues found by classmates. Advanced Testing: Hands-on session applying PromptFoo for complex scenarios, including multi-turn conversation testing using JSON objects for regression. Tool Exposure: Alternative testing tool.

Day 8: Tool Exploration & Post-Launch Monitoring

Post-Launch Tools: Demo and discussion of tools used for monitoring and maintaining LLM models pre- and post-launch (e.g., Arato wrapper). New Tool Assignment: Introduction to Agenta (a comparable, alternative LLM testing platform). Homework: Explore and evaluate Agenta to apply foundational testing concepts learned from PromptFoo. Research other AI testing tools in the market (consulting mindset).

Week 5 (Career Acceleration)

Day 9: Agenta Review & LinkedIn Strategy

Tool Comparison: Reviewing homework findings on Agenta, applying foundational concepts (Evals, variables) learned from PromptFoo to a new platform. Career Branding: Strategies for content creation and influence building on LinkedIn. Using generative AI tools (e.g., Claude, ChatGPT) as brainstorming partners for posts, while avoiding generic copy-paste content. Accomplishments: Workshop focused on drafting AI LLM testing accomplishment statements for resumes/profiles, quantifying the business impact of skills learned. Homework: Post tailored AI testing content on LinkedIn and engage (comment/repost) with classmates' posts.

Day 10: Final Optimization & Interview Prep

Final Profile Optimization: Updating LinkedIn profiles and resumes with core AI testing skills (prompt engineering, red teaming, hallucination detection, token consumption). Interview Preparation: Review of common AI testing interview questions (e.g., scaling tests, verifying factual responses, token consumption, security, testing LLMs with other LLMs). Wrap-up: Final remarks, community engagement commitment, and discussion of post-course resources.

Apply for April Cohort

100% money-back guarantee.

What you'll achieve in 5-weeks

Week 1 (Foundations and Tool Mastery)

Day 1: AI Fundamentals & Setup

Introduction: Course rules, setting up the permanent Discord community channel. Theory: LLM basics, transformer architecture, differences between traditional software testing and AI system testing. Hands-on: Environment setup (local and cloud models). Initial interactive model exploration comparing local (LM Studio) and commercial (OpenAI, Anthropic) models using the same prompt. Vulnerabilities: Introduction to the seven unique AI testing challenges (e.g., security, hallucination, bias). Homework: Complete environment setup and design 3+ test prompts targeting the vulnerabilities.

Day 2: PromptFoo Basics

Tool Introduction: Learning PromptFoo for systematic AI testing. Shift to hands-on, Q&A, and group exercises (minimal presentations). Configuration: Overview of PromptFoo's configuration (YAML structure), including providers (LLMs), prompts, and initial deterministic assertions (pass/fail checks). Practice utilizing variables within prompts. Integration: Testing commercial and local models via PromptFoo. Homework: Practice building test suites and reviewing assertions documentation.

Week 2 (Foundations and Tool Mastery)

Day 3: Prompt Engineering and Cost Evaluation

Prompt Engineering: Defining the rules and constraints of the system (System Prompt) and crafting effective test inputs (User Prompt). Using AI (LLMs) to generate effective test prompts. Evaluation: Hands-on workshop on LLM cost evaluation (budgeting) by running prompts against multiple models to compare cost per request. Organization: Structuring the testing framework using file-based prompt configurations.

Day 4: Advanced Assertion & Career Prep

Advanced Testing: Deep dive into assertions, particularly Model-Graded Assertions (MGA), where an LLM acts as a judge (LLM Rubric) to evaluate output quality (relevancy, factuality). Testing using CSV-based files for structured test data. Career Start: Introduction to LinkedIn Personal Branding; documenting early achievements and incorporating AI testing keywords (e.g., prompt engineering, LLM testing) to profiles. Homework: Review PromptFoo Red Teaming documentation.

Week 3 (Application Testing and Advanced Techniques)

Day 5: Red Teaming Concepts

Equator Point: Course halfway review. Red Teaming: Defining red teaming as simulating adversarial inputs (like a comprehensive baseline report) to find vulnerabilities (e.g., security, bias). Discussion of vulnerability frameworks like the OWASP Top 10 for AI. Strategy: Understanding Red Teaming workflow (defining strategy, execution, analysis) and configurations. Comparison of red teaming types (Small, Large, XXL/Extensive).

Day 6: Testing a Real Application (Red Team Web App)

Application Architecture: Reviewing the high-level architecture of the application (Orchestrator, Guard LLM, specialized LLMs, knowledge bases like Jira/Confluence/Figma). Testing Mode: Focusing on end-to-end black box exploratory testing via the application's chat interface. Using the provided "Source of Truth" as acceptance criteria. Bug Reporting: Hands-on exercise reporting and documenting bugs in ClickUp, including reproduction steps and linking them to specific AI vulnerabilities.

Week 4 (Application Testing and Advanced Techniques)

Day 7: Red Teaming Execution & Triage

Application Setup: Finalizing the Red Teaming configuration by inputting a comprehensive application context (main purpose, features, system rules) into PromptFoo. Group Triage: Teams exchange reported bugs and attempt to reproduce and validate issues found by classmates. Advanced Testing: Hands-on session applying PromptFoo for complex scenarios, including multi-turn conversation testing using JSON objects for regression. Tool Exposure: Alternative testing tool.

Day 8: Tool Exploration & Post-Launch Monitoring

Post-Launch Tools: Demo and discussion of tools used for monitoring and maintaining LLM models pre- and post-launch (e.g., Arato wrapper). New Tool Assignment: Introduction to Agenta (a comparable, alternative LLM testing platform). Homework: Explore and evaluate Agenta to apply foundational testing concepts learned from PromptFoo. Research other AI testing tools in the market (consulting mindset).

Week 5 (Career Acceleration)

Day 9: Agenta Review & LinkedIn Strategy

Tool Comparison: Reviewing homework findings on Agenta, applying foundational concepts (Evals, variables) learned from PromptFoo to a new platform. Career Branding: Strategies for content creation and influence building on LinkedIn. Using generative AI tools (e.g., Claude, ChatGPT) as brainstorming partners for posts, while avoiding generic copy-paste content. Accomplishments: Workshop focused on drafting AI LLM testing accomplishment statements for resumes/profiles, quantifying the business impact of skills learned. Homework: Post tailored AI testing content on LinkedIn and engage (comment/repost) with classmates' posts.

Day 10: Final Optimization & Interview Prep

Final Profile Optimization: Updating LinkedIn profiles and resumes with core AI testing skills (prompt engineering, red teaming, hallucination detection, token consumption). Interview Preparation: Review of common AI testing interview questions (e.g., scaling tests, verifying factual responses, token consumption, security, testing LLMs with other LLMs). Wrap-up: Final remarks, community engagement commitment, and discussion of post-course resources.

Apply for April Cohort

You have a 100% money-back guarantee.

Benefits You Won't Find Anywhere Else

Why learning AI & LLM Testing is a must for Every QA in 2025?

Benefits You Won't Find Anywhere Else

Lifetime Community Access

Lifetime Community Access

Join our Discord community with 600+ QA professionals.

Ongoing support from instructors and alumni.

Regular follow-up sessions and career guidance.

Recorded Sessions

Recorded Sessions

All sessions recorded and can be accessed up to for 1 year.

Review program materials and session recording anytime.

Never miss important concepts.

Real Resume Experience

Real Resume Experience

Internship opportunities with Stella Foster
(AI Startup Project)

Reference real US-based company projects in interviews.

Get personalized CV review.

Career Transformation Support

Career Transformation Support

Resume and LinkedIn profile optimization.

Interview preparation and skill positioning.

Network with fellow AI testing professionals.

Who Should Attend?

01

QA Engineers, SDETs, and Test Leads ready to upskill for the AI era.

02

Automation experts are curious about testing non-deterministic AI systems.

03

Tech professionals looking to future-proof their careers as AI reshapes quality engineering.

Who Should Attend?

01

QA Engineers, SDETs, and Test Leads ready to upskill for the AI era.

02

Automation experts are curious about testing non-deterministic AI systems.

03

Tech professionals looking to future-proof their careers as AI reshapes quality engineering.

Who Should Attend?

01

QA Engineers, SDETs, and Test Leads ready to upskill for the AI era.

02

Automation experts are curious about testing non-deterministic AI systems.

03

Tech professionals looking to future-proof their careers as AI reshapes quality engineering.

Who Should Attend?

01

QA Engineers, SDETs, and Test Leads ready to upskill for the AI era.

02

Automation experts are curious about testing non-deterministic AI systems.

03

Tech professionals looking to future-proof their careers as AI reshapes quality engineering.

  • A recruiter messaged me saying she is impressed with my resume and skills in AI testing during the second week of the course. I got a new job as a QA Manager at that startup. All thanks to this AI & LLM Testing course at Engenious University

    Sofiia Tsapchuk

    Quality Manager at Company Sage

  • My team failed to validate our AI system 4 times - we were stuck and didn't know where to start. After the AI Testing course, I now have the tools and confidence to eliminate unknown risks. I can finally set up proper AI testing frameworks that leadership trusts.

    Hershal Walton,

    Product Manager at TIAA

  • This training has been amazing fun, interactive, and full of hands-on exercises instead of boring lectures. I actually felt sad it was ending! I came here because I saw job descriptions for AI Test Engineers that I couldn’t even understand — and I realized I needed to catch up.

    Shiva Srinivasan

    QA Lead at Clari Health

  • The sessions showed me how to easily test different LLM models which is a game-changer for protecting company data in a closed environment. The hands-on approach helped me see how to apply AI testing directly in my work, and it sparked new ideas for improving our apps and APIs at GoTo Foods.

    Sanchit Agarwal

    QE Architect at GoTo Foods

  • The sessions showed me how to easily test different LLM models which is a game-changer for protecting company data in a closed environment. The hands-on approach helped me see how to apply AI testing directly in my work, and it sparked new ideas for improving our apps and APIs at GoTo Foods.

    Sanchit Agarwal

    QE Architect at GoTo Foods

  • My team failed to validate our AI system 4 times - we were stuck and didn't know where to start. After the AI Testing course, I now have the tools and confidence to eliminate unknown risks. I can finally set up proper AI testing frameworks that leadership trusts.

    Hershal Walton

    Product Manager at TIAA

  • A recruiter messaged me saying she is impressed with my resume and skills in AI testing during the second week of the course. I got a new job as a QA Manager at that startup. All thanks to this AI & LLM Testing course at Engenious University

    Sofiia Tsapchuk

    QA Manager at Company Sage

  • This training has been amazing fun, interactive, and full of hands-on exercises instead of boring lectures. I actually felt sad it was ending! I came here because I saw job descriptions for AI Test Engineers that I couldn’t even understand — and I realized I needed to catch up.

    Shiva Srinivasan

    QA Lead at Clari Health

Instructors

Instructors

Tagir Fahriev

Tagir Fahriev

Tagir has 10 years of experience in the tech industry; Senior Android Engineer in Platform team.

Tagir has 10 years of experience in the tech industry; Senior Android Engineer in Platform team.

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Amanda Curtis

Amanda Curtis

Amanda is a QA leader and Lemonade Tech founder, she helps teams cut through tech overwhelm with responsible AI adoption.

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Jaime Mantilla

Jaime Mantilla

Jaime is a seasoned IT professional with 14+ years of experience in Software Engineering, Quality Assurance, and Automation.

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100% Money-Back Guarantee: If you're not satisfied by Week 1, claim a full refund, no questions.


Seats are limited to 40 registrants. Secure your spot today.

100% money back guarantee

100% Money-Back Guarantee: If you're not satisfied by Week 1, claim a full refund, no questions.


Seats are limited to 40 registrants. Secure your spot today.

FAQs

FAQs

What is the AI Career Accelerator program?

What is the duration of the training?

Who is this program for?

What will I achieve by completion?

What’s the weekly breakdown?

Are there prerequisites?

What makes this program different?

Which modules include RAG pipelines, grounding validation, and hallucination detection?

Do we cover data quality validation and production monitoring (data drift, model drift, feedback loops)?

Is there coverage beyond text-only LLMs (e.g., CV or audio)?

Do we work with agent frameworks like AutoGen, LangGraph, or CrewAI?

What portfolio deliverables will I graduate with?

What are the system requirements to join?

What career paths does this program prepare me for?

How do I apply?

Is there a Payment Plan Option?

Will Engenious University help with Career Search?

What is the AI Career Accelerator program?

What is the duration of the training?

Who is this program for?

What will I achieve by completion?

What’s the weekly breakdown?

Are there prerequisites?

What makes this program different?

Which modules include RAG pipelines, grounding validation, and hallucination detection?

Do we cover data quality validation and production monitoring (data drift, model drift, feedback loops)?

Is there coverage beyond text-only LLMs (e.g., CV or audio)?

Do we work with agent frameworks like AutoGen, LangGraph, or CrewAI?

What portfolio deliverables will I graduate with?

What are the system requirements to join?

What career paths does this program prepare me for?

How do I apply?

Is there a Payment Plan Option?

Will Engenious University help with Career Search?

What is the AI Career Accelerator program?

What is the duration of the training?

Who is this program for?

What will I achieve by completion?

What’s the weekly breakdown?

Are there prerequisites?

What makes this program different?

Which modules include RAG pipelines, grounding validation, and hallucination detection?

Do we cover data quality validation and production monitoring (data drift, model drift, feedback loops)?

Is there coverage beyond text-only LLMs (e.g., CV or audio)?

Do we work with agent frameworks like AutoGen, LangGraph, or CrewAI?

What portfolio deliverables will I graduate with?

What are the system requirements to join?

What career paths does this program prepare me for?

How do I apply?

Is there a Payment Plan Option?

Will Engenious University help with Career Search?

Apply for April cohort

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+1 234 234 23 23

university@engenious.io

© 2026 Engenious Inc. (c) All rights reserved

Contact us

Privacy Policy

Terms of Service

+1 234 234 23 23

university@engenious.io