9:00am - 3:30pm

June 26- June 30, 2017

​​​​​Applied Analytics Camp

About the Camp

Join us to explore the exciting and interesting field of Analytics!

Major Features

  • Students that have taken a course that covers basic statistics or a recommendation from a math teacher.
  • Rising high school juniors and seniors, but rising sophomores may also apply.

This one-week introductory course is about using data and being able to gain insight into the data. The first day of this course is a review of basic statistics and an introduction to simple linear regression using SAS Enterprise Guide. Businesses use regression to predict such things as future sales, stock prices, and productivity gains resulting from a training program.

On the second day of this course is an introduction to Data Mining and  learning
SAS Enterprise Miner, a popular data mining tool. Data Mining is the process of analyzing data from different perspectives and summarizing it into useful information. This includes descriptive analysis, cluster analysis, and predictive modeling using decision trees.

The third day will complete Data Mining and introduce students to visualization tools such as SAS
Visual Analytics or Tableau.  It involves the creation and study of the visual representation of data.  Effective visualization helps users in analyzing and reasoning about data and evidence.

On the fourth and fifth days, students will be given an opportunity to work on real-world data with the guidance of the instructors. They will close the course by presenting their findings.

Who can Apply?

Dates:  Monday, June 27 - Friday July 1 (5days)

Time:   9:00am to 3:30pm. (Non-Residential program).
            Bring your own lunch, you may also purchase

            lunch in the cafeteria.

Fee:     No fee! Thanks to the SAS Institue for their


Application deadline
Friday, June 16, 2017
Contact Us

Dates, Times, Program Fee

  • A Bryant Analytics certificate for participation!
  • Hands-on class instruction using SAS software, a leading Analytics software package
  • Well-designed workshops and activities associated with analytics learning