GIT+GitHub: Todo un sistema de control de versiones de cero
★ 4.8 rated · $9.99
Build Robust AI Agents | Monitor Production AI Agents | Build Custom Evals | Master Galileo AI | For Engineers
$9.99 with coupon (list $149.99 — save $140.00, 93% off)
Coupon Verified: October 2, 2026 · click Claim Coupon to apply the discount code
Our verdict: worth it — as long as the Development skills on the syllabus match what you actually want to learn. The regular price for LLM AI Agent Evaluations and Observability with Galileo AI on Udemy is $149.99. With the coupon code on this page, that falls to $9.99 — a saving of $140.00, or 93% off the standard rate Spread across 7h 30m of on-demand video, that works out to roughly $1.33 per hour of content — cheaper than a single chapter of most printed Development textbooks.
A cheap price means nothing if the material is thin — here the syllabus is organized around usable outcomes. Henry Habib and The Intelligent Worker walk you through design an LLM observability plan: what to log, how to structure traces, and how to make failures diagnosable, build evaluation datasets with realistic inputs, expected behavior, metadata, and slices for edge cases and regressions, and run repeatable Galileo AI experiments to compare models, prompts, and agent versions on consistent test sets — skills meant to be used, not just watched. It has already been taken by 853 students and holds a 4.6-star average from verified reviews, which suggests the content holds up once learners actually apply it.
Check the prerequisites before you commit: Basic Python knowledge; Basic AI Agent building knowledge. Best suited to learners who already have footing in Development. Plan for roughly 7h 30m of on-demand video at your own pace. Lessons are delivered in English.
Practical skills and outcomes you'll gain from LLM AI Agent Evaluations and Observability with Galileo AI — taken from the official Udemy syllabus for Development learners.
Design an LLM observability plan: what to log, how to structure traces, and how to make failures diagnosable.
Build evaluation datasets with realistic inputs, expected behavior, metadata, and slices for edge cases and regressions.
Run repeatable Galileo AI experiments to compare models, prompts, and agent versions on consistent test sets.
Implement custom eval metrics for generation quality, groundedness, safety, and tool correctness (beyond accuracy).
Apply LLM-as-judge scoring with rubrics, constraints, and spot checks to reduce evaluator bias and drift.
Debug agent failures using traces to pinpoint breakdowns in retrieval, planning, tool use, or response synthesis.
Set up production monitoring in Galileo with signals, dashboards, and alerts for regressions and silent failures.
Use eval results to prioritize fixes, validate improvements, and prevent quality or safety regressions over time.
What you need before enrolling in LLM AI Agent Evaluations and Observability with Galileo AI — prerequisites as listed by the instructor on Udemy.
Basic Python knowledge
Basic AI Agent building knowledge
Can work with Jupyter Notebooks
No prior observability experience needed
The full official description of LLM AI Agent Evaluations and Observability with Galileo AI — curriculum, teaching approach, and everything included with this Udemy coupon.
Important: this coupon may not function properly in private/incognito browsing mode. Please use a standard browser window and consider temporarily disabling any ad blockers or VPN services.
Common queries about this coupon, pricing, and enrollment. Answers reflect our last check on October 2, 2026.
★ 4.8 rated · $9.99
★ 4.8 rated · $9.99
★ 4.7 rated · $9.99
★ 4.5 rated · $12.99
★ 4.1 rated · $9.99
★ 4.1 rated · $9.99
We may earn a commission when you purchase through our links. Learn more