Supervised Machine Learning Procedures Using SAS® Viya® in SAS® Studio
This course covers a variety of machine learning techniques that are performed in a scalable and in-memory execution environment. The course provides hands-on experience with SAS Visual Data Mining and Machine Learning through SAS Studio, a user interface for SAS programming. The machine learning techniques include logistic regression, decision tree and ensemble of trees (forest and gradient boosting), neural networks, support vector machine, factorization machine, and Bayesian networks.
The self-study e-learning includes:
Who should attendData analysts, data miners, mathematicians, statisticians, data scientists, citizen data scientists, qualitative experts, and others who want an introduction to supervised machine learning for predictive modeling
Before attending this course, you should have, at minimum, an introductory-level familiarity with basic statistics. SAS experience is helpful but not required. Coding experience is helpful but not required.
This course addresses SAS Viya software.
Introduction to SAS Viya, Data Preparation, and Exploration
|Title||Duration||Access Period||Language||Fee||Add to Cart|
|Supervised Machine Learning Procedures Using SAS Viya in SAS Studio (PDF + 20 virtual lab hours)||14.0 hours||180 days from order date||English||960 USD|
|Dates||Location||Time||Language||Fee||Add to Cart|
|29 NOV-02 DIC 2022||Live Web||12:00 PM-03:30 PM CST||English||1,450 USD|
|24-27 ENE 2023||Live Web||12:00 PM-03:30 PM CST||English||1,450 USD|
|02-05 MAY 2023||Live Web||12:00 PM-03:30 PM CDT||English||1,450 USD|
|29 NOV-02 DEC 2022||Live Web||01:00 PM-04:30 PM EST||English||1,600 USD|
|24-27 JAN 2023||Live Web||01:00 PM-04:30 PM EST||English||1,600 USD|
|02-05 MAY 2023||Live Web||01:00 PM-04:30 PM EDT||English||1,600 USD|
|29 NOV-02 DEC 2022||Live Web||01:00 PM-04:30 PM EST||English||1,920 CAD|
|24-27 JAN 2023||Live Web||01:00 PM-04:30 PM EST||English||1,920 CAD|
|02-05 MAY 2023||Live Web||01:00 PM-04:30 PM EDT||English||1,920 CAD|
|24-27 JAN 2023||Live Web||03:00 PM-06:30 PM -02||English||3.000 BRL|
|02-05 MAI 2023||Live Web||02:00 PM-05:30 PM -03||English||3.000 BRL|