Deploying Machine Learning Models

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Course Overview

In this course we will learn about Recommender Systems (which we will study for the Capstone project), and also look at deployment issues for data products. By the end of this course, you should be able to implement a working recommender system (e.g. to predict ratings, or generate lists of related products), and you should understand the tools and techniques required to deploy such a working system on real-world, large-scale datasets. This course is the final course in the Python Data Products for Predictive Analytics Specialization, building on the previous three courses (Basic Data Processing and Visualization, Design Thinking and Predictive Analytics for Data Products, and Meaningful Predictive Modeling). At each step in the specialization, you will gain hands-on experience in data manipulation and building your skills, eventually culminating in a capstone project encompassing all the concepts taught in the specialization.

Course FAQs

What are the prerequisites for 'Deploying Machine Learning Models'?

Prerequisites for this continuing education class are set by University of California San Diego. Most professional development online classes benefit from some prior knowledge. Please check the provider's page for specific requirements.

Will I receive a certificate for this CE class?

Yes, upon successful completion, University of California San Diego typically offers a shareable certificate to showcase your new skills and fulfill your continuing education requirements.

How long does this online course take to complete?

Completion times for online continuing education courses vary. The provider's website will have the most accurate estimate of the time commitment needed.