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Information Technology Graduate Certificate, Advanced Analytics Using SAS®

School of Business and Technology

The Advanced Analytics Using SAS® graduate certificate is an academic certificate jointly offered by Capella University and approved by SAS. It prepares learners to advance in the data analytics field by providing the knowledge needed to effectively manage, analyze, and visually represent complex data. Learners develop and demonstrate advanced skills in data mining, data modeling, forecasting, analysis, and visual representation. Using both structured and unstructured data, learners formulate and solve complex business problems using advanced data analysis strategies. Learners also obtain and demonstrate knowledge in applying SAS analytics tools such as Enterprise Guide®, Enterprise Miner™, Forecast Server, Rapid Predictive Modeler, Text Miner, Visual Analytics, and Visual Statistics. In addition and throughout the program, learners are given the opportunity to earn exam vouchers for SAS certifications.

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Five Required Courses

 

 

20 quarter credits

ANLT5050 *
Concepts of Data Mining

In this course, learners develop their skills in creating a predictive model. Learners apply data mining algorithms, models, and data mining modeling techniques to test, fit, and implement an algorithm and/or model with appropriate tools. Learners practice interpreting results to find an application for those results. Finally, learners apply control, feedback, and evaluation approaches to enhance, continue, or retire the algorithm or model using big data. Prerequisite(s): ANLT5030. Graduate certificate learners in Advanced Analytics Using SAS® are exempt from this prerequisite.

4 quarter credits
ANLT5060 *
Applied Forecasting

In this course, learners evaluate forecast model outcomes to solve organizational problems. Learners examine the impact of time and data latency on forecasting, and practice identifying patterns in the output of forecast models. Learners also apply forecasting techniques in their communication with stakeholders.  Prerequisite(s): ANLT5030.

4 quarter credits
ANLT5070 *
Text Mining

Learners in this course gain an understanding of the early stages of text mining. Learners examine document management practices, text-scraping techniques, and various methods for modeling their findings as they solve text-based mining problems. Prerequisite(s): ANLT5030. Graduate certificate learners in Advanced Analytics Using SAS® are exempt from this prerequisite.

4 quarter credits
ANLT5080 *
Advanced Analytics and Modeling

Learners in this course demonstrate advanced practice in applying the analytic life cycle. Learners examine approaches to visual analytics and are introduced to geospatial data techniques. Learners also apply their analytic skills to current organizational problems and apply analytic solution scoring and project management skills for effective team performance. Prerequisite(s): ANLT5050.

4 quarter credits
ANLT5100 *
Visual Analytics

In this course, learners articulate the value of visualization to telling the analytic story to stakeholders. Learners explore the appropriate presentation of types of data and apply best practices for the design of effective visualizations. Learners also develop skills for presenting data to stakeholders in a succinct and relevant manner. Prerequisite(s): ANLT5030. 

4 quarter credits

 

 

Total

 

 

20 quarter credits

* Denotes courses that have prerequisite(s). Refer to the descriptions for further details.