Welcome to our Introduction Series for Cloudera Education. The following contains excerpts from DSCI:272 - Predicting with MLOps on Cloudera AI, that is part of our full OnDemand Training Library.

The complete library is available for purchase. Upon completion you will see a path to continue your Cloudera training journey. Many courses include hands-on labs and the OnDemand library comes with 100 hands-on lab hours to practice the concepts and exercises taught. Please enjoy this section of your selected course to help you on your data journey.

Disclaimer - The following descriptions and objectives are for the full course.

Overview

Enterprise data science teams need collaborative access to business data, tools, and computing resources required to develop and deploy machine learning workflows. Cloudera AI, part of the Cloudera platform, provides the solution, giving data science teams the required resources.

This course covers machine learning workflows and operations using Cloudera AI. Participants explore, visualize, and analyze data. You will also train, evaluate, and deploy machine learning models.

The course walks through an end-to-end data science and machine learning workflow based on realistic scenarios and datasets from a fictitious technology company. The demonstrations and exercises are conducted in Python (with PySpark) using Cloudera AI.

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Course Length

This course includes approximately 8.5 hours of video lectures and demonstrations. 

You will need your own environment to work on the labs. The labs will take approximately 7 hours to complete.

What to expect

The course is designed for data scientists who need to understand how to utilize Cloudera AI and the Cloudera platform to achieve faster model development and deliver production machine learning at scale. Data engineers, developers, and solution architects who collaborate with data scientists will also find this course valuable.