Completion Certificate for Machine Learning Engineering for Production (MLOps)

December 28, 2021

Approximately 2 months at 10 hours a week to complete

Tomas Kepes's account is verified. Coursera certifies their successful completion of DeepLearning.AI Machine Learning Engineering for Production (MLOps) Specialization.

Course Certificates Completed

Introduction to Machine Learning in Production

Machine Learning Data Lifecycle in Production

Machine Learning Modeling Pipelines in Production

Deploying Machine Learning Models in Production

4.7 (3,384 ratings)

69K Students Enrolled

What you will learn

Design an ML production system end-to-end: project scoping, data needs, modeling strategies, and deployment requirements.
Establish a model baseline, address concept drift, and prototype how to develop, deploy, and continuously improve a productionized ML application.
Build data pipelines by gathering, cleaning, and validating datasets. Establish data lifecycle by using data lineage and provenance metadata tools.
Apply best practices and progressive delivery techniques to maintain and monitor a continuously operating production system.