Title	Level	Training Formats
Faculty Development Program: Shaping an Analytics Curriculum (A SAS & Open Source Approach) The Faculty Development Program (FDP) teaches you fundamental concepts and relevant techniques in analytics and machine learning using a powerful mix of SAS and open-source programming languages. The course also enables you to explore academic and collaborative opportunities with SAS in the area of advance analytics for designing better curriculum and effective pedagogy. Please note: This FDP is only for eligible Professors and members of Academic Institutions.	0 No level
Interactive Machine Learning in SAS Viya This course provides a theoretical foundation for SAS Visual Data Mining and Machine Learning, as well as hands-on experience using the tool through the SAS Visual Analytics interface. The course uses an interactive approach to teach you visualization, model assessment, and model deployment while introducing you to a variety of machine learning techniques.	4 Advanced
Machine Learning with SAS This short course uses an interactive approach to introduce you to visualization, model assessment, and model deployment while introducing you to a variety of machine learning techniques. 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 Interactive Machine Learning in SAS Viya course. Attendees who complete this short course and wish to complete the associated comprehensive training may be eligible for a discount.	1 Beginner
SAS Viya and Python Integration for Machine Learning In this course, you learn to use the Python API to take control of SAS Cloud Analytic Services (CAS) actions from Jupyter Notebook. You learn to upload data into the in-memory distributed environment, analyze data, and create predictive models in CAS using familiar Python functionality via the SWAT (SAS Wrapper for Analytics Transfer) package. You then learn to download results to the client and use native Python syntax to compare models.	3 Intermediate
SAS Viya and R Integration for Machine Learning In this course, you learn to use the R API to take control of SAS Cloud Analytic Services (CAS) actions from Jupyter Notebook. You learn to upload data into the in-memory distributed environment, analyze data, and create predictive models in CAS using familiar R functionality via the SWAT (SAS Wrapper for Analytics Transfer) package. You then learn to download results to the client and use native R syntax to compare models.	3 Intermediate