SAS Academy for Data Science: SAS Advanced Analytics Professional
Description
The SAS Certified Advanced Analytics Professional program represents Level 2 of the SAS Academy for Data Science. Students learn a variety of machine learning and predictive modeling techniques, and how to apply the techniques to big distributed and in-memory data sets. Students also learn about experimentation in business, optimization, and time series forecasting, as well as the essential communication skills necessary to deliver value to the organization.
The course work, hands-on practice, and projects help prepare students for the three exams needed to become a SAS Certified Advanced Analytics Professional. Exams are included.
Learn how to
- Apply machine learning and predictive mode…
Foire aux questions (FAQ)
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The SAS Certified Advanced Analytics Professional program represents Level 2 of the SAS Academy for Data Science. Students learn a variety of machine learning and predictive modeling techniques, and how to apply the techniques to big distributed and in-memory data sets. Students also learn about experimentation in business, optimization, and time series forecasting, as well as the essential communication skills necessary to deliver value to the organization.
The course work, hands-on practice, and projects help prepare students for the three exams needed to become a SAS Certified Advanced Analytics Professional. Exams are included.
Learn how to
- Apply machine learning and predictive modeling techniques to big distributed and in-memory data sets.
- Detect patterns in your data.
- Set up and run business experiments.
- Optimize your data.
- Use time-series forecasting techniques.
- Effectively communicate results and recommendations to executive-level management.
Who should attendIndividuals with a least six months of programming experience in SAS or another programming language, and at least six months of experience using mathematics, statistics, or both in a business environment. A master's degree or higher in a quantitative or technical field is recommended but not required.
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