The first part of the course teaches performing Machine Learning at Scale using the popular Apache Spark framework. This course is intended for data scientists and software engineers, and assumes attendees have little or no previous experience with Machine Learning. This course explores popular machine learning algorithms from the ground up. Students will explore Apache Spark essentials, core machine learning concepts, regressions, classifications, clustering and more.
Learning Objectives
This “skills-centric” course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Throughout the program, working in a hands-on learning environment guided by our expert instructor, students will Learn popular machine learning algorithms, their applicability, and limitations Practice the application of these methods in the Spark machine learning environment Learn practical use cases and limitations of algorithms Will explore not just the related APIs, but will also learn the theory behind them Work with real world datasets from Uber, Netflix, Walmart, Prosper, etc.
Framework Connections
The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):
Work Roles
Feedback
If you would like to provide feedback on this course, please e-mail the NICCS team at NICCS@mail.cisa.dhs.gov. Please keep in mind that NICCS does not own this course or accept payment for course entry. If you have questions related to the details of this course, such as cost, prerequisites, how to register, etc., please contact the course training provider directly. You can find course training provider contact information by following the link that says “Visit course page for more information...” on this page.