SAS Visual Text Analytics

Title Level Training Formats
FDP -Shaping an AI & ML curriculum for Business
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
FDP-Shaping a Data Science Curriculum
This FDP supports developing a data science program that covers a variety of topics and enables students to acquire the skills that industry is looking for their employees to have. The FDP helps universities develop a pool of talent with the range of analytical and technology skills to work in a data-rich business environment.

1 Beginner Live Web Classroom
Text Analytics with SAS
This short course introduces SAS Visual Text Analytics which enables you to uncover insights hidden within unstructured data using the combined power of natural language processing, machine learning, and linguistic rules. Explore components of Visual Text Analytics: parsing, concept derivation, topic derivation and sentiment analysis on an introductory basis.Please note: This is a taster course providing an overview of the listed SAS tool(s) and capabilities. For more comprehensive training, please consider the SAS Visual Text Analytics in SAS Viya course. Attendees who complete this short course and wish to complete the associated comprehensive training may be eligible for a discount.

3 Intermediate Classroom Live Web Classroom
SAS Visual Text Analytics in SAS Viya
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 Visual Text Analytics: parsing, concept derivation, topic derivation, text categorization, and sentiment analysis. Documents are parsed and analyzed to reveal dominant themes in the document collection. Sophisticated linguistic queries are constructed to satisfy specific information needs. An integrated solution is developed using information extracted from subject matter expert rules, combined with machine learning results for model and rule-based topics and categories. The course includes hands-on use of SAS Viya in a distributed computing environment.

3 Intermediate Classroom Live Web Classroom e-Learning