AI Evals Certification Course for Engineers & Product Managers
Vivian Aranha
Founder & AI Instructor at School of AI
This course is popular
5 people enrolled last week.
AI Evals for Engineers & PMs: Measure, Improve, and Ship Reliable AI
Learn on your schedule with this self-paced course featuring pre-recorded sessions. Enjoy lifetime access, so you can revisit and reinforce your learning whenever needed.
AI products are fundamentally different from traditional software. They are probabilistic, non-deterministic, and constantly evolving as models, prompts, and data change. Because of this, traditional testing methods like unit tests and QA checklists are no longer enough.
Teams building AI systems—whether chatbots, RAG systems, copilots, or autonomous agents—often struggle with a critical question: How do we know if our AI system is actually improving or silently getting worse?
This course teaches engineers and product managers how to design modern AI evaluation systems that measure quality, detect regressions, and guide product decisions. You will learn how to evaluate LLM outputs, score AI behavior using structured rubrics, automate evaluation pipelines, and operationalize evals in CI/CD workflows.
By the end of the course, you will understand how leading AI teams ship reliable AI products using evaluation frameworks that combine datasets, metrics, automated scoring, human feedback, and monitoring dashboards.
What you’ll learn
Build production-ready AI evaluation systems to measure LLM quality, detect regressions, and ship reliable AI products.
Identify what to evaluate in LLMs, RAG systems, and AI agents
Define measurable success criteria for AI behavior
Convert vague goals into evaluation signals
Design representative evaluation datasets
Capture edge cases and failure scenarios
Create benchmarks that reflect real user behavior
Use metrics like correctness, relevance, faithfulness, and safety
Build scoring rubrics for human and automated evaluation
Align AI metrics with product goals
Build automated evaluation pipelines
Compare models, prompts, and system versions
Detect regressions across releases
Score retrieval quality and groundedness
Evaluate tool usage and agent planning
Measure multi-step reasoning performance
Add evaluation gates to CI/CD pipelines
Build dashboards for AI quality monitoring
Use eval data to guide product decisions
Learn directly from Vivian
Vivian Aranha
AI architect with 2.2M+ learners, building enterprise-grade agentic systems
Who this course is for
AI Engineers & ML Engineers
Building LLM applications, RAG systems, or AI agents who need reliable ways to measure & improve model behavior.AI Engineers & ML Engineers
Building LLM applications, RAG systems, or AI agents who need reliable ways to measure & improve model behavior.Tech Leads & AI Startup Founders
Leading teams building AI prods who need to operationalize evaluation before deploying models to production.
What's included
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Production-Ready AI Evaluation Framework
Learn how to design evaluation systems used by modern AI teams to measure quality and prevent regressions.
Evaluate LLMs, RAG Systems, and AI Agents
Go beyond simple prompts and learn how to evaluate complex AI architectures and multi-step systems.
Hands-On Labs and Real Evaluation Pipelines
Build datasets, scoring systems, automated evaluators, and dashboards used in real AI products.
Automated AI Evaluation with LLM-as-Judge
Use AI to evaluate AI at scale using structured prompts, scoring rubrics, and automated pipelines.
Ship AI Products with Confidence
Learn how to use evaluation metrics to guide release decisions, model upgrades, and product strategy.
Maven Guarantee
This course is backed by the Maven Guarantee. Students are eligible for a full refund up until the halfway point of the course.
Course syllabus
32 lessons • 10 projects
Week 1
Day 1 — Foundations of AI Evaluation
Day 2 — Metrics, Scoring & Human Feedback
Day 3 — Automated LLM-Based Evaluation
Week 2
Day 4 — Evaluating RAG, Tools & Agents
Day 5 — Production Evals, Monitoring & Decision-Making
Schedule
Projects
4-6 hrs
Async content
6-8 hrs
Frequently asked questions
$20
USD
2 days left to enroll