Cloud Machine Learning Engineering and MLOps
Building Cloud Computing Solutions at Scale,
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.
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Length | 4 weeks |
Effort | 3 weeks of study, 3-5 hours/week |
Starts | Jul 3 (44 weeks ago) |
Cost | $49 |
From | Duke University via Coursera |
Instructor | Noah Gift |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science Programming IT & Networking |
Tags | Data Science Machine Learning Cloud Computing Information Technology |
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Rating | Not enough ratings |
---|---|
Length | 4 weeks |
Effort | 3 weeks of study, 3-5 hours/week |
Starts | Jul 3 (44 weeks ago) |
Cost | $49 |
From | Duke University via Coursera |
Instructor | Noah Gift |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science Programming IT & Networking |
Tags | Data Science Machine Learning Cloud Computing Information Technology |
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