[VIP DOWNLOAD] AI Evals For Engineers & PMs – No.1 Course at Maven

AI Evals For Engineers & PMs – A Practical Course for Building Better AI

AI Evals For Engineers & PMs stands as a leading course on Maven for technical builders. It focuses on improving AI systems through structured, data-driven evaluation. Instead of guessing what works, you learn how to measure and refine performance with clarity.

This program targets engineers and technical product managers who build AI applications. If you code regularly, you will feel comfortable with the exercises. Moreover, the flipped classroom format keeps learning interactive and practical.

If you often explore high-quality WSO Downloads, this training fits well among advanced technical resources. You can also discover more professional courses through WSO Download Hub while expanding your AI expertise.

Why AI Evaluation Matters More Than Ever

Modern AI systems produce stochastic outputs. Therefore, traditional testing methods often fail. Many teams struggle with subjective judgments and unclear metrics.

AI Evals For Engineers & PMs removes that uncertainty. It teaches you how to evaluate LLM applications across their full lifecycle. As a result, you reduce business risk and improve reliability.

You will learn how to answer critical questions, such as:

How to test outputs that vary each time
How to change prompts without breaking other features
Which metrics truly matter
How to start without existing user data
Whether automated evaluation can be trusted

Because these issues appear in real projects, the course stays highly practical.

A Hands-On, Flipped Learning Experience

This course does not rely on endless slides. Instead, it combines recorded lectures with live office hours. You attend sessions twice a week for four weeks. During that time, you complete coding exercises and structured assignments.

All sessions are recorded for lifetime access. In addition, students receive over nine hours of office hour Q&A. This ensures direct interaction with instructors.

You also gain access to a private Discord community with more than 1,000 members. Through this network, you can ask technical questions and exchange insights.

Deep Dive Into the Curriculum

AI Evals For Engineers & PMs covers evaluation from fundamentals to production monitoring. Each lesson builds on the previous one. Consequently, you develop a complete evaluation framework.

Fundamentals and Lifecycle Evaluation

First, you explore why evaluation shapes business outcomes. You examine common failure modes in LLM systems. Then, you learn lifecycle-based evaluation from development to production.

You also implement basic instrumentation and observability tools. Error analysis becomes a central focus early in the course.

Systematic Error Analysis

Next, you practice generating synthetic data to bootstrap testing. This step proves valuable when you lack real users. You also learn annotation strategies and quantitative review techniques.

Importantly, you translate findings into actionable improvements. Therefore, analysis directly improves product quality.

Implementing Effective Evaluations

In this section, you define metrics using both code-based approaches and LLM-as-a-judge systems. You build automated evaluation pipelines during practical exercises.

Dataset organization also receives strong attention. Clean structure leads to better comparisons and consistent benchmarks.

Collaborative Evaluation Workflows

Evaluation rarely happens alone. For that reason, the course teaches team-based workflows. You explore statistical methods for measuring agreement across reviewers.

You also practice alignment techniques in breakout exercises. These methods reduce bias and inconsistency.

Architecture-Specific Evaluation

AI systems differ by design. Therefore, evaluation must adapt. You learn how to assess RAG systems for retrieval accuracy and factual correctness.

The course also covers:

Multi-step pipeline testing
Tool usage evaluation
Multi-turn conversation analysis
Multi-modal system assessment

Through targeted test suites, you learn to isolate and fix architecture-specific weaknesses.

Production Monitoring and Continuous Evaluation

Once your AI reaches production, monitoring becomes essential. You implement traces, spans, and session tracking for observability.

You also set up automated evaluation gates in CI/CD pipelines. This protects system quality during rapid iteration.

Moreover, you design dashboards to monitor performance trends. Continuous comparison across experiments ensures stable improvement.

Human Review and Cost Optimization

Human review remains crucial for high-quality AI systems. Therefore, the course teaches strategic sampling and efficient interface design.

You build continuous feedback loops that strengthen model alignment. Over time, this creates a powerful data flywheel.

Cost optimization also receives detailed coverage. You quantify value versus expense in LLM applications. Additionally, you explore intelligent model routing based on query complexity.

Powerful Resources Included

AI Evals For Engineers & PMs offers more than lectures. Every student receives:

Lifetime access to recordings and materials
Ten months of unlimited access to the AI Eval Assistant
A 150+ page course reader based on an O’Reilly draft
Four homework assignments with solutions
Professionally edited video chapters
A certificate of completion

You may also retake future cohorts, depending on enrollment terms. Furthermore, the Maven Guarantee allows a refund before the halfway point.

These resources ensure long-term value beyond the live sessions.

What You Will Achieve

By completing AI Evals For Engineers & PMs, you gain structured tools for diagnosing AI errors. Instead of chasing random improvements, you prioritize high-impact fixes.

You will learn how to bootstrap testing with synthetic data. Later, you will leverage real user data more effectively. Through automation and human review, you create trustworthy evaluation systems.

Most importantly, you align AI outputs with your business goals and quality standards. This alignment prevents costly failures and wasted development cycles.

Who Should Enroll?

This course suits engineers and technical PMs who actively build AI systems. It works best for those comfortable with coding and experimentation.

If you want to outperform competitors, systematic evaluation gives you a strong advantage. Rather than relying on guesswork, you rely on measurable insights.

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