Trusted by 500+ Al Companies
Courses & Training From exam prep to hands-on Al QA mastery.
Build your expertise in testing Al, LLMs, and RAG systems with ISTQB-certified and enterprise-
level programs — led by senior Al QA professionals.
Exam Prep
Practitioner
Advanced
On-site
Remote
Course Categories
ISTQB Al Testing
Official certification preparation courses
- Automated pipeline testing
- Build verification testing
- Deployment validation workflows
ISTQB Al Testing
Official certification preparation courses
- Automated pipeline testing
- Build verification testing
- Deployment validation workflows
Regression Testing
99.5% bug prevention
- Automated regression test suites
- Visual regression testing
- Cross-browser compatibility testing
Regression Testing
99.5% bug prevention
- Automated pipeline testing
- Build verification testing
- Deployment validation workflows
SaaS Testing
100% tenant isolation
- Multi-tenant data isolation testing
- Tenant-specific configuration validation
- Scalability testing per tenant
SaaS Testing
100% tenant isolation
- Automated pipeline testing
- Build verification testing
- Deployment validation workflows
Certified Tester Al Testing (CT-Al)
3 Days
Core Topics:
Focus:
Testing Al systems and machine learning workflows with confidence - covering both technical and ethical aspects.
- Al basics and the "Al effect"; narrow, general, and super Al
- Al vs conventional systems and key Al frameworks
- Quality characteristics unique to Al systems — flexibility, autonomy, bias, ethics, safety
- Machine Learning (ML): workflows, supervised/unsupervised/reinforcement learning, neural networks
- Data preparation, labeling, dataset quality, and concept drift
- ML performance metrics and their limitations
- Testing Al systems: non-determinism, bias, and complexity challenges
- Al-specific test methods: adversarial, metamorphic, A/B, and pairwise testing
- Testing documentation and environment setup
- Using Al to assist testing: defect prediction, regression optimization, test case generation
Unique Value:
- Focused on understanding and validating Al system internals
- Ethical lens: bias, transparency, fairness, explainability, safety, and ethical risk
- Detect and mitigate model drift, data poisoning, and non- deterministic behavior
Certified Tester Generative Al (CT-GenAI)
3 Days
Focus:
Testing with and of Generative Al systems - including large language models (LLMs) and retrieval-augmented generation (RAG) pipelines.
Core Topics:
- Prompt engineering tailored for QA workflows
- Hallucination detection and grounding validation
- Bias, safety, compliance, and privacy in GenAl outputs
- Evaluating RAG systems using the RAGAS framework
- Leveraging GenAl for automation, analysis, and reporting
- Managing Al-specific risks: hallucinations, bias, and data leakage
- Integrating GenAl tools into CI/CD and QA pipelines
Unique Value:
- Hands-on use of Generative Al for improving QA efficiency
- Practical focus on LLM/RAG evaluation and risk management
- Emphasis on transparency, guardrails, and responsible Al
Al Tester Foundation Bootcamp
5 Days
Focus:
Equip QA professionals with foundational Al testing skills — combining core QA principles with modern Al automation and data validation.
Enhanced Content Highlights:
- Comprehensive Al Testing Fundamentals: Understanding ML workflows, identifying unique Al QA challenges
- Modern Automation Focus: Hands-on Playwright for Al web apps, API testing for ML services, and mobile Al testing
- Al-Powered Testing Tools: Practical use of ChatGPT and Claude for automated test design and script generation
- Data-Driven QA Excellence: Synthetic data creation, data validation pipelines, dataset quality assurance
- Real-World Labs: End-to-end chatbot testing, recommendation engine validation, ML pipeline QA, CI/CD automation
Learning Outcomes:
Graduates will confidently test Al applications, design Al-aware test strategies, build automation frameworks, and master Al-powered test generation.
Deliverables:
Al testing toolkit, Playwright automation suite, data validation scripts, prompt engineering guide, and career roadmap.
Advanced Al QA (LLM & RAG) Professional Program
10 Days
Focus:
Master enterprise-level Al QA — including large language model (LLM) evaluation, retrieval-augmented generation (RAG) testing, and compliance frameworks.
Enhanced Content Highlights:
- Advanced LLM Evaluation: DeepEval, RAGAS metrics, custom evaluation logic, and LLM-as-a-Judge patterns
- Comprehensive RAG Testing: Vector DB validation, retrieval accuracy, chunk optimization
- Hallucination Detection & Mitigation: Factual consistency checks and attribution validation
- Self-Healing Automation: Playwright + Al integration, dynamic selector healing
- Compliance Excellence: EU Al Act frameworks, GDPR validation, bias mitigation
- Enterprise-Scale Architecture: Real-time monitoring, governance, and alerting
Learning Outcomes:
Participants will architect end-to-end LLM/RAG QA frameworks, master safety validation, design self-healing test automation, and lead organizational Al QA transformations.
Deliverables:
Advanced Al testing framework, evaluation library, compliance toolkit, self-healing automation platform, and governance playbook.
All Courses
Fair Lending
ISTQB Al Testing
Official certification preparation courses
20 Hours
$399
Enroll
Fair Lending
ISTQB Al Testing
Official certification preparation courses
20 Hours
$399
Enroll
Fair Lending
ISTQB Al Testing
Official certification preparation courses
20 Hours
$399
Enroll
Fair Lending
ISTQB Al Testing
Official certification preparation courses
20 Hours
$399
Enroll
Fair Lending
ISTQB Al Testing
Official certification preparation courses
20 Hours
$399
Enroll
Fair Lending
ISTQB Al Testing
Official certification preparation courses
20 Hours
$399
Enroll
Learning Outcomes
Vector Databases
Pinecone, Weaviate, Milvus
Model Validation
Comprehensive testing of GPT-4, Claude, Liama, and custom LLMs for accuracy, consistency, and performance.
Define Test Objectives
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Define Test Objectives
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Frequently Asked Questions
Do I need prior Al experience?
We conduct a discovery call before each workshop to understand your current tools, frameworks, and specific challenges. Workshop content is then customized to include relevant examples, code samples, and scenarios that match your technology stack and domain requirements.
Is the course instructor-led or self-paced?
Absolutely! We frequently create multi-day custom bootcamps by combining different workshop tracks. We can design a comprehensive 3-5 day program that covers multiple aspects of AI QA, from foundations through advanced topics like governance and CI/CD integration.
Will I receive a certificate?
The most effective workshops include a mix of QA engineers, developers, product owners, and team leads. This diverse perspective ensures better knowledge sharing and helps align the entire team on AI testing approaches. We recommend 15-25 participants for optimal interaction.
What practical tools will I learn?
Yes, all workshop participants receive comprehensive materials including slide decks, lab repositories, code samples, and reference guides. While we don’t typically record live sessions to encourage open discussion, we provide detailed documentation and examples that serve as ongoing references.