• Online, Self-Paced
Course Description

From self-driving cars to predicting stock prices, machine learning has an exciting range of applications. BigML, due to its ease of use, makes these algorithms widely accessible. This course outlines machine learning fundamentals and how these are applied in BigML.

You'll start by examining various machine learning algorithm categories and the kinds of problems they're used to solve. You'll then investigate the classification problem and the process involved in training and evaluating such models. Next, you'll examine linear regression and how this can help predict a continuous value.

Moving on, you'll explore the concept of unsupervised learning and its application in clustering, Principal Component Analysis (PCA), and generating associations. Finally, you'll recognize how all of this comes together when using BigML to significantly simplify the building and maintenance of your machine learning models.

Learning Objectives

{"discover the key concepts covered in this course"}

Framework Connections

The materials within this course focus on the Knowledge Skills and Abilities (KSAs) identified within the Specialty Areas listed below. Click to view Specialty Area details within the interactive National Cybersecurity Workforce Framework.