Cloud Machine Learning Engineering and MLOps
About this course
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.
90/100
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- What the provider tells you
- 39/45
- Who stands behind it
- 35/35
- How complete the listing is
- 16/20
Scores how much the provider publishes and who stands behind it — not how well it is taught.
What you'll learn
- understanding of machine learning engineering concepts
- skills to create machine learning applications
- experience with AutoML techniques
- knowledge of MLOps, Edge Machine Learning, and AI APIs
- ability to build a Flask web application for serving predictions
Course objectives
- apply software development best practices to machine learning projects
- develop efficient solutions using AutoML
- gain hands-on experience with cloud computing in data science
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