courses ·
LLMs in Production
1 certified
A working LLM demo is not a production system. Latency spikes, cost explodes, quality drifts, edge cases break things. This course teaches you to ship LLMs to real users: monitoring, evals, RAG, cost control, observability. The 2026 production stack.
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- 01
Start here: what this course is about
Welcome to LLMs in ProductionRead first. ~3 minutes.
- 02
Start here: what is LLMOps?
What is LLMOps? - Databricks↗Databricks explains the discipline. The gap between LLM demos and production systems.
- 03
The LLMOps stack: tracing, evals, monitoring
What is LLMOps? LLM Operations Guide - MLflow↗MLflow's overview of the production stack. Tracing, evaluation, prompt management, monitoring.
- 04
Cost and latency in practice
How to Monitor Cost and Latency in Production LLM Systems↗Token-level, model-level, app-level tracking. A poorly tuned prompt can 10x your bill.
- 05
Observability tools compared (neutral)
Top 5 LLM and Agent Observability Tools - MLflow↗MLflow's comparison: Phoenix, Langfuse, LangSmith, Braintrust, MLflow. No marketing, just trade-offs.
- 06
RAG: making LLMs use your data
Retrieval-Augmented Generation: A Practical Guide to RAG Architecture↗Most production LLM apps use RAG. How retrieval-augmented generation works and when to use it.
- 07
Production-grade RAG
The Enterprise RAG Architecture Guide↗Chunking, embeddings, vector DBs, reranking, hybrid search. The stack that actually works.
- 08
Anthropic's lessons from production
Anthropic: Building Production AI Agents (ZenML LLMOps Database)↗What Anthropic learned shipping Claude Code and enterprise deployments. Real production insights, not theory.
- 09
Structured outputs: production reliability
The guide to structured outputs and function calling with LLMs↗How structured outputs replace fragile regex parsing. OpenAI JSON mode, Anthropic tools, Google schemas.
- 10
457 real case studies
LLMOps in Production: 457 Case Studies of What Actually Works - ZenML↗ZenML analyzed 457 production LLM deployments. What worked, what failed. Real signal, not pitch decks.
- 11
State of the art: 2026 LLMOps tools
Top 15 LLMOps Tools for Building AI Applications in 2026 - DataCamp↗DataCamp's neutral catalog of 15 LLMOps tools. Evaluation, observability, prompt management. Pick what fits your stack.
- 12
Closing: what to take with you
Closing: From Demo to DurableWrap-up. ~3 minutes.
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