Machine Learning Engineering for Production (MLOps)

Welcome to our event celebrating the launch of Machine Learning Engineering for Production (MLOps) Specialization featuring AI leaders in MLOps.

Topics we plan to cover:

  • To what extent does the role of Data Scientist or MLE involve MLOps?
  • How is MLOps actually implemented in an industry setting? Is there some kind of a framework people use?
  • Is MLOps suitable for early-stage startups or only teams with enough resources as the big tech companies do?
  • The latest trends on MLOps and how will the future of it evolve.
  • What do you see as the biggest challenges for MLOps adoption?
  • Apart from taking courses, what are some of the other resources or activities might recommend to learners interested in gaining practical experience with MLOps?


  • Andrew Ng, Founder, DeepLearning.AI
  • Robert Crowe, TensorFlow Developer Engineer, Google
  • Laurence Moroney, AI Advocate, Google
  • Chip Huyen, Adjunct Lecturer, Stanford University
  • Rajat Monga, co-founder, Stealth Startup; Former lead of TensorFlow, Google
  • Event moderator: Ryan Keenan, Director of Product, DeepLearning.AI

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Machine Learning Engineering for Production (MLOps)