• Classroom
  • Online, Instructor-Led
Course Description

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):

Specialty Areas

  • Cyber Defense Analysis
  • Cyber Defense Infrastructure Support
  • Cyber Investigation
  • Digital Forensics
  • Exploitation Analysis
  • Network Services
  • Risk Management
  • Software Development
  • Test and Evaluation
  • Threat Analysis
  • Training, Education, and Awareness
  • Vulnerability Assessment and Management