Course guide

MLOps learning path

Reviews for turning machine-learning knowledge into production practice.

Our short answer

Machine Learning in Production (Coursera/DeepLearning.AI) is the structured anchor of this path. Full Stack Deep Learning covers overlapping ground with a stronger engineering culture; IBM’s AI Engineering certificate fits if you want one credential that bundles ML and deployment.

Use the full reviews below to compare fit, workload, and current course details before you choose.

MLOps

Machine Learning in Production (DeepLearning.AI)

DeepLearning.AI

3.6 / 5

Best for: Early-career ML practitioners who want a conceptual framework for designing and scoping production ML systems

Certificate requires a Coursera (~$59/month Coursera Plus) or DeepLearning.AI Pro subscription as of August 2026; audit availability unknown — check current pricing Read review →

Large Language Models

Full Stack Deep Learning / LLM Bootcamp (The Full Stack)

The Full Stack

4.2 / 5

Best for: Software engineers and ML practitioners who want to build and ship LLM-powered products end-to-end

Free — recorded lectures and slides, no paid tier Read review →

Foundations

IBM AI Engineering Professional Certificate

IBM / Coursera

4.2 / 5

Best for: Developers and data practitioners with working Python who want broad coverage of ML/DL frameworks plus modern LLM/GenAI engineering skills

Coursera subscription around $49/month as of August 2026; individual courses free to audit — check current pricing Read review →

Find a course that fits you

Reviews on this page verified 2026-08-22; each links its own dated sources.