SAS AI & Machine Learning Certification Program

Overview
Prerequisites
Course Outline

The SAS AI & Machine Learning Certification Program is designed for data professionals who want to learn artificial intelligence and machine learning techniques using SAS Viya. Students learn to train and deploy supervised machine learning models, classify image data and analyze text with deep learning, uncover hidden insights within unstructured data, develop and score time series forecasting models, and perform several useful optimization techniques in SAS Viya.

The coursework and preparation sessions help prepare candidates for the three exams needed to earn a SAS Certified Professional: Artificial Intelligence and Machine Learning credential.

This course can help prepare you for the following certification exams: SAS Certified Specialist: Machine Learning Using SAS Viya 3.4, SAS Certified Specialist: Natural Language and Computer Vision, and SAS Certified Specialist: Forecasting and Optimization

Learn how to

Apply the analytical life cycle to business need.
Prepare and explore data for analytical model development.
Train models using deep learning techniques.
Import and transform image data for analysis.
Explore collections of text documents to discover key insights.
Build and share custom pipelines for large-scale forecasting analyses.
Refine forecast models to improve forecast accuracy.
Solve optimization problems commonly encountered in industry.
Identify and formulate appropriate approaches to solving optimization problems.

Who should attend

Programmers, business analysts, or statisticians with experience using SAS Viya and writing programs in SAS or other programming languages

Formats available	Standard Duration (duration can vary, see event schedule for details)
Classroom:	14 days
Live Web Classroom:	28 half-day session(s)	System Requirements
e-Learning:	70 hours/1 year license

Before you participate in this program, it is recommended that you have the following experience and knowledge:

It is recommended that you have programming experience using SAS, Python, or R. You can gain programming knowledge in the SAS Programming 1: Essentials course.
Candidates should also have some experience with the visual interfaces in SAS Viya. You can learn about those interfaces in the SAS Visual Statistics in SAS Viya: Interactive Model Building or SAS Visual Analytics 1 for SAS Viya: Basics course.
It is helpful to have conceptual understanding of regression models, which you can gain by completing the Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression course.
It is also helpful to have conceptual understanding of neural network models, which you can gain by completing the Neural Networks: Essentials or Neural Network Modeling course.