SAS

This course provides a review of the majority of topics in the SAS 9.4 Base Programming Performance-Based Exam. It addresses the four exam content areas: Accessing and Creating Data Structures, Managing Data, Generating Reports and [...]
ETDP1F | Duration 1 day | No scheduled terms
This class teaches you how to tune your SAS programs for faster execution, especially those that access relational database tables using SAS/ACCESS interfaces or SAS Viya data connectors.
MC1V2 | Duration 2 days | No scheduled terms
This course focuses on using the SAS macro facility to design, write, and debug macro programs, with an emphasis on understanding how programs that contain macro code are processed.
SVSO35 | Duration 2 days | No scheduled terms
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. This course is appropriate for users of SAS Visual [...]
SVTA35 | Duration 2 days | No scheduled terms
SAS Visual Text Analytics enables you to uncover insights hidden within unstructured data using the combined power of natural language processing, machine learning, and linguistic rules. This course explores the five components of [...]
VSTU1C | Duration 1 day | No scheduled terms
This course is for users who do not have SAS programming experience but need to access and prepare data, and present summarized results. This course focuses on using flows, a point-and-click tool in SAS Studio that visualizes data [...]
YVA11D | Duration 2 days | No scheduled terms
This course provides an introduction to data preparation, data discovery, and report creation in SAS Visual Analytics.
YVA21D | Duration 2 days | No scheduled terms
This course describes advanced features of data preparation, analytics, and report creation in SAS Visual Analytics.
ADML35 | Duration 3 days | No scheduled terms
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 [...]
AEMOSI | Duration 1 day | No scheduled terms
This course introduces the basics for integrating R programming and Python scripts into SAS and SAS Enterprise Miner. Topics are presented in the context of data mining, which includes data exploration, model prototyping, and [...]
EG182 | Duration 2 days | No scheduled terms
This course is for users who do not have SAS programming experience but need to access, manage, and summarize data from different sources, and present results in reports and graphs. This course focuses on using the menu-driven tasks [...]
EG282 | Duration 2 days | No scheduled terms
This course is intended for experienced SAS Enterprise Guide users who want to learn more about advanced SAS Enterprise Guide techniques. It focuses on using the Query Builder within SAS Enterprise Guide, including manipulating [...]
AGLM42 | Duration 3 days | No scheduled terms
This course teaches you how to analyze linear mixed models using the MIXED procedure. A brief introduction to analyzing generalized linear mixed models using the GLIMMIX procedure is also included.
PG1V2 | Duration 3 days | No scheduled terms
This course is for users who want to learn how to write SAS programs to access, explore, prepare, and analyze data. It is the entry point to learning SAS programming for data science, machine learning, and artificial intelligence. It [...]
PG2V2 | Duration 2 days | No scheduled terms
This course is for those who need to learn data manipulation techniques using the SAS DATA step and procedures to access, transform, and summarize data. The course builds on the concepts that are presented in the SAS(R) Programming [...]
STBA42 | Duration 2 days | No scheduled terms
The course focuses on Bayesian analyses using the PHREG, GENMOD, and MCMC procedures. The examples include logistic regression, Cox proportional hazards model, general linear mixed model, zero-inflated Poisson model, and data [...]
VBBF35 | Duration 3 days | No scheduled terms
Decision trees and tree-based ensembles are supervised learning models used for problems involving classification and regression. This course covers everything from using a single tree to more advanced bagging and boosting ensemble [...]

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