Chevron Left
Back to DevOps, DataOps, MLOps

Learner Reviews & Feedback for DevOps, DataOps, MLOps by Duke University

4.1
stars
145 ratings

About the Course

Learn how to apply Machine Learning Operations (MLOps) to solve real-world problems. The course covers end-to-end solutions with Artificial Intelligence (AI) pair programming using technologies like GitHub Copilot to build solutions for machine learning (ML) and AI applications. This course is for people working (or seeking to work) as data scientists, software engineers or developers, data analysts, or other roles that use ML. By the end of the course, you will be able to use web frameworks (e.g., Gradio and Hugging Face) for ML solutions, build a command-line tool using the Click framework, and leverage Rust for GPU-accelerated ML tasks. Week 1: Explore MLOps technologies and pre-trained models to solve problems for customers. Week 2: Apply ML and AI in practice through optimization, heuristics, and simulations. Week 3: Develop operations pipelines, including DevOps, DataOps, and MLOps, with Github. Week 4: Build containers for ML and package solutions in a uniformed manner to enable deployment in Cloud systems that accept containers. Week 5: Switch from Python to Rust to build solutions for Kubernetes, Docker, Serverless, Data Engineering, Data Science, and MLOps....

Top reviews

ND

Aug 22, 2024

Great learning resources, concise presentations, and clear explanations of all topics

RV

Jun 24, 2024

Extremely usefull to understand concepts of MLOps, containers, CI/CD

Filter by:

26 - 37 of 37 Reviews for DevOps, DataOps, MLOps

By Vaishnavi K

•

Apr 19, 2024

good

By ALISHA N K

•

Jun 29, 2024

na

By Gitika C

•

Sep 16, 2024

.

By Runjhun T

•

Dec 1, 2024

VERY USEFUL

By Ilaiyaraja S

•

Jan 2, 2025

Excellent

By Prasad V

•

Nov 28, 2024

Great

By SAYAN G

•

Sep 27, 2023

Great

By Vaisakh S N

•

Nov 13, 2024

good

By SANJAY B

•

Aug 3, 2023

Very fast approach to teach, lost in some videos too

By Michel C

•

Feb 3, 2025

Quiz on aspects that are not taught yet. A lot of material is links to the author's books. Seems like trying to sell books. A lot of material is also linked to articles that are very long and requires 3-4 hours to read all of it but instructor rates it as a 10 minute read. The linked articles are updated/changed. There are quizes to check understanding but often before the material and there's no good labs to teach you how to set up an app and test you. Recommend checking Andrew Ng's courses. The labs instruction videos and labs are excellent examples of how to put together a good course.

By Mykhaylo K

•

Feb 13, 2025

Provides some nuggets of insight, but overall not worth it - typical regurgitated corporate training.

By Lars D

•

Feb 11, 2025

Wild mix of videos lacking an overall structure. Endless repetition of basic stuff like Makefiles.