The 3 best MLOps courses in 2026
We compared 3 MLOps courses across 1 providers and ranked the top 3 by learner ratings and enrollment. Updated automatically as ratings and catalogs change.
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Learn to deploy ML models to production using the Sovereign Rust Stack—a pure Rust implementation with zero Python runtime dependencies. This hands-on course teaches you to work with three critical model formats (GGUF, SafeTensors, APR), implement MLOps pipelines with CI/CD and observability, and deploy models across GPU, CPU, WebAssembly, and edge targets. Through real-world projects including a Python-to-Rust transpiler (Depyler), browser-based speech recognition (Whisper.apr), and LLM inference benchmarking (Qwen), you'll master format conversion, cryptographic model signing, and performan
AWS and DeepLearning.AI course on LLM architecture, fine-tuning, and deployment.
Design production ML systems: data pipelines, deployment, monitoring, and lifecycle management.
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Quick comparison
| # | Course | Provider | Rating | Duration | Price |
|---|---|---|---|---|---|
| 01 | Production ML with Hugging Face | Coursera | — | 4h | Subscription |
| 02 | Generative AI with Large Language Models | Coursera | 4.8 | 16h | Subscription |
| 03 | Machine Learning Engineering for Production (MLOps) | Coursera | 4.6 | 80h | Subscription |