Chevron Left
返回到 Cloud Machine Learning Engineering and MLOps

学生对 Duke University 提供的 Cloud Machine Learning Engineering and MLOps 的评价和反馈

4.5
星
87 个评分

课程概述

Welcome to the fourth course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will build upon the Cloud computing and data engineering concepts introduced in the first three courses to apply Machine Learning Engineering to real-world projects. First, you will develop Machine Learning Engineering applications and use software development best practices to create Machine Learning Engineering applications. Then, you will learn to use AutoML to solve problems more efficiently than traditional machine learning approaches alone. Finally, you will dive into emerging topics in Machine Learning including MLOps, Edge Machine Learning and AI APIs. This course is ideal for beginners as well as intermediate students interested in applying Cloud computing to data science, machine learning and data engineering. Students should have beginner level Linux and intermediate level Python skills. For your project in this course, you will build a Flask web application that serves out Machine Learning predictions....

热门审阅

筛选依据：

1 - Cloud Machine Learning Engineering and MLOps 的 17 个评论（共 17 个）

创建者 Maciej L

•

Mar 31, 2023

Once again, disappointing repetitions. Weak syllabus structure. It is based chiefly on Mr Gift's practical know-how. He seems to me like a Cloud/DevOps evangelist really, and a fan of black-box ML solutions.

创建者 Oleksandr S

•

Feb 10, 2023

The course is an introduction with a lot of repetitions from other courses of this specialization. I don't like how the information is prepared. A lot of videos are lectures from the instructor's work in university and from other courses (e.g. courses from Udacity). Don't think that certificate really costs that money.

创建者 Perikles R

•

Jun 20, 2024

The lectures are not easy to follow and reproduce as the platforms and tools have changed since the time of the publication. Also, the lectures have been hastily put together and it shows: Very often it is like a live session (Will it work? Will it not work?) vs a recorded class. The writing on screen is also sloppy - powerpoint would definitely help.

创建者 Yağızhan A A

•

Feb 8, 2022

Amazing teacher and perfect mixture of necessary informations. It was a privilage to learn from him, i recommend this course for every ML Engineer.

创建者 Aaron D

•

Nov 1, 2022

Great Intro into DevOps and MLOps for beginners, Also good explanation and practical application examples

创建者 Sergio A C G

•

Jul 9, 2021

Excellent course, very concise but complete, if possible a second version would be ideal

创建者 Matias L M

•

Jan 4, 2024

Insightful, complete, in detail. Recommended

创建者 David M

•

Aug 30, 2025

Absolutamente útil

创建者 Pardon C

•

Jul 16, 2022

Great course

创建者 谭中意

•

Sep 19, 2021

cool course

创建者 CG - D S J

•

Nov 10, 2024

Excelente

创建者 GUDI H .

•

Mar 16, 2025

good

创建者 Ivan O C

•

Jun 27, 2021

Nice content and complete due that the course show the three main/popular options for MLOPs solutions: AWS, GCP and Azure... I prefer explanations using slides due they are more systematic and when is possible try to avoid some demos in an spontaneous way...

创建者 Sylvain P

•

Feb 8, 2023

Really enjoyed the whole specialization! The 3rd course on data engineering has some editing and redundancy issues, but otherwise, this very hands-on and to-the-point approach was fantastic. Many thanks.

创建者 Alson Y

•

Jun 1, 2022

Great course to know practical ideas and concepts.

创建者 dumebi j

•

Nov 17, 2021

good

创建者 Omid K

•

Oct 13, 2024

The covered topics are mostly interesting. Though, the course could benefit from a revisit as there are many parts that feel redundant, overall structure of the course feels unclear etc.