SAS Visual Statistics

名称 水平 培训形式
FDP - Shaping a Business Analytics Curriculum
This outline is provisional and subject to change.The Faculty Development Program (FDP) teaches you fundamental concepts and relevant techniques in self-service data preparation, business visualization, and modeling using a powerful mix of point-and-click visual SAS tools. The course also enables you to explore academic and collaborative opportunities with SAS in the area of advanced analytics for designing better curriculum and effective pedagogy.

0 No level Live Web Classroom
FDP - Shaping an Analytics and Machine Learning Curriculum
This outline is provisional and subject to change.The Faculty Development Program (FDP) teaches you fundamental concepts and relevant techniques in analytics and machine learning using a powerful mix of point-and-click visual SAS tools, including visual analytics, visual data mining and machine learning, and text analytics. The course also enables you to explore academic and collaborative opportunities with SAS in the area of advanced analytics for designing better curriculum and effective pedagogy.

0 No level Live Web Classroom
SAS Viya Overview New
This course provides an introduction to the applications in SAS Viya and discusses how each application is used in each phase of the SAS Analytics Life Cycle: Data, Discovery, Deployment, and Orchestration.

1 Beginner e-Learning
SAS Visual Statistics in SAS Viya: Interactive Model Building New
This course introduces SAS Visual Statistics for building predictive models in an interactive, exploratory way. Exploratory model fitting is a critical step in modeling big data.

The classroom and Live Web course is appropriate for users of SAS Visual Analytics in SAS Viya 3.5. In e-learning, there is a course for users of SAS Visual Analytics in SAS Viya 3.5, and there is also a course for users of SAS Visual Analytics in SAS Viya 2020.1.

3 Intermediate Live Web Classroom e-Learning
Data Mining Techniques: Predictive Analytics on Big Data New
This course introduces applications and techniques for assaying and modeling large data. The course also presents basic and advanced modeling strategies, such as group-by processing for linear models, random forests, generalized linear models, and mixture distribution models. Students perform hands-on exploration and analyses using tools such as SAS Enterprise Miner, SAS Visual Statistics, and SAS In-Memory Statistics.

3 Intermediate Live Web Classroom e-Learning
Advanced Machine Learning Using SAS Viya New
This course teaches you how to optimize the performance of predictive models beyond the basics by implementing various data munging and wrangling techniques. The course continues the development of supervised learning models that begins in the 使用SAS Viya的机器学习 course and extends it to ensemble modeling. Running unsupervised learning and semi-supervised learning models is also discussed. In this course, you learn how to do feature engineering and clustering of variables, and how to preprocess nominal variables and detect anomalies. This course uses Model Studio, the pipeline flow interface in SAS Viya that enables you to prepare, develop, compare, and deploy advanced analytics models. Importing and running external models in Model Studio is also discussed, including open-source models. SAS Viya automation capabilities at each level of machine learning are also demonstrated, followed by some tips and tricks with Model Studio.

The self-study e-learning includes:

  • Annotatable course notes in PDF format.
  • Virtual lab time to practice.

4 Expert e-Learning