MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.
This course uses Model Studio, the pipeline flow interface in SAS Viya that enables you to prepare, develop, compare, and deploy advanced analytics models. You learn to train supervised machine learning models to make better decisions on big data. The SAS applications used in this course make machine learning possible without programming or coding.
Syllabus
WEEK 1
Course Overview
In this module, you meet the instructor and learn about course logistics, such as how to access the software for this course.
Getting Started with Machine Learning using SAS® Viya®
In this module, you learn how you can meet today's business challenges with machine learning using SAS® Viya®. You start working on the project that runs throughout the course.
WEEK 2
Data Preparation and Algorithm Selection
In this module, you learn to explore the data and finish preparing the data for analysis. You also learn some general considerations for selecting an algorithm.
WEEK 3
Decision Trees and Ensembles of Trees
In this module, you learn to build decision tree models as well as models based on ensembles, or combinations, of decision trees.
WEEK 4
Neural Networks
In this module, you learn to build neural network models.
WEEK 5
Support Vector Machines
In this module, you learn to build support vector machine models.
WEEK 6
Model Deployment
In this module, you learn how to select the model that best meets the requirements of your business challenge and put the model into production. You also learn about managing the model over time.
WEEK 7
Additional Resources and Practice Exam
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.