LLM Observability and Cost Management: Langfuse, Monitoring — 90% Off Coupon

Production-Ready LLM Monitoring with Langfuse, Cost Optimization, Tracing, Alerting & Real-World Debugging Patterns

4.7 108 students enrolledCreated by Paolo DichoneLast updated: 🌐 English

Course Overview — Key Details

A quick-reference summary of the most important course details: provider, instructor, difficulty, duration, and what the coupon covers.

•Course Title: LLM Observability and Cost Management: Langfuse, Monitoring
•Provider: Udemy (listed via CourseSpeak)
•Instructor: Paolo Dichone
•Coupon Verified On: February 20, 2026
•Difficulty Level: All Levels
•Category: IT & Software
•Subcategory: Large Language Models (LLM)
•Duration: 2h 30m of on-demand video
•Language: English
•Access: Lifetime Access · Mobile & TV compatible
•Certificate: Certificate of completion included
•Top Learning Outcomes: Implement production-grade LLM observability using Langfuse and understand tracing concepts · Reduce LLM API costs by 50-80% using semantic caching, model routing, and prompt optimization · Debug LLM applications in minutes using traces, spans, and proper instrumentation patterns
•Prerequisites: Basic Python programming skills (variables, functions, classes) · Familiarity with LLM APIs (OpenAI, Anthropic, or similar) - you should have made at least a few API calls before
•Coupon: Click REDEEM COUPON below to apply discount

What You'll Learn

Skills and competencies you'll gain from this Udemy course:

✓Implement production-grade LLM observability using Langfuse and understand tracing concepts .
✓Reduce LLM API costs by 50-80% using semantic caching, model routing, and prompt optimization .
✓Debug LLM applications in minutes using traces, spans, and proper instrumentation patterns .
✓Set up cost alerts and monitoring dashboards that catch budget issues before they escalate .
✓Build production-ready code patterns for token tracking, cost calculation, and PII redaction.

Course Requirements & Prerequisites

Background knowledge or tools recommended before starting this course:

•Basic Python programming skills (variables, functions, classes)
•Familiarity with LLM APIs (OpenAI, Anthropic, or similar) - you should have made at least a few API calls before
•A code editor (VS Code recommended) and Python 3.9+ installed

About This Udemy Course

Full course description including curriculum, tools covered, and learning methodology:

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About the Instructor

This course is taught by Paolo Dichone. For full instructor bio, credentials, and other courses they teach, visit the instructor profile on Udemy.

•Instructor: Paolo Dichone
•Field: IT & Software
•Teaching Style: Practical, project-based learning (as described in course curriculum)

Is the LLM Observability and Cost Management: Langfuse, Monitoring Coupon Worth It?

LLM Observability and Cost Management: Langfuse, Monitoring is a it & software course offered on Udemy by instructor Paolo Dichone, spanning 2h 30m of on-demand content. It holds a 4.7/5 rating from over 108 enrolled students.

Through CourseSpeak, you can access this course with a 90% discount coupon. The coupon was last verified on February 20, 2026. Udemy coupons are time-limited and claimed on a first-come basis — we recommend redeeming as soon as possible.

✓ Our Take: Based on the rating (4.7/5) and enrollment numbers (108 students), this course appears well-regarded in its category. Use the coupon to access it at a significantly reduced price — and judge for yourself using Udemy's 30-day money-back guarantee.

Course Rating Summary

Aggregate rating data sourced from Udemy as of February 2026. For individual student reviews, visit the course page directly.

4.7
108 ratings
5 stars
75%
4 stars
15%
3 stars
6%
2 stars
2%
1 star
2%

* Rating distribution is estimated. For exact per-star counts, visit the Udemy course page.

Frequently Asked Questions

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