SDS Bootcamp Courses


A solid foundation in vocabulary of healthcare, Statistics, Python, SAS, and R programming is critical for success in the SDS graduate programs and to prepare for a career in the field of data science. The SDS has developed Four online, self-paced training courses to ensure that students have a strong foundation to support their graduate coursework. All SDS students enrolled are eligible to take these training courses. Several instructors may require successful completion of the bootcamps as part of specific classes. 

As an asynchronous course, students can register for the Summer 2023 and Fall 2023 SDS Bootcamps beginning of May 2023. Students currently enrolled in the Spring 20223semester must complete the bootcamp by April 15th, 2023.  


Introduction to SAS for Health Analytics

A self-paced introduction to the basics of programming in SAS. This course of study is tied to a specific course in the HIA program: HCIP 6102 Healthcare Analytics. 

Introduction to R for Data Science

A self-paced introduction to R programming for data analysis using RStudio environment. The modules covered include R data structures, functions, and packages, importing and cleaning data, and data visualization in R.

Overview of Statistics for Data Science

A self-paced course to help prepare students with the base level of statistics knowledge for success in the data science program. The modules in this course cover an introduction to statistics, probability, and probability distributions. Descriptive statistics and hypothesis testing are also covered in this course.

Vocabulary Training Course

Students are required to complete a pre-program, self-directed online training module in basic concepts and vocabulary in health, medical nomenclature, and computer science terminology. The training course provides students a grounding in vocabulary and core concepts needed for success in our foundational courses.

This training course is designed as a series of units within three larger modules. Each unit has an associated quiz. Students must complete all modules in order to receive the required certificate of completion. Entering students are encouraged to complete this training PRIOR to arrival on campus in August. Providing proof of its completion is a requirement early on in HCIP 6380 (Introduction to Health Informatics). 



All data science bootcamps can be found in Canvas. Students can register for the individual bootcamps using the registration link below. 



The bootcamps are modularized and self-contained. The courses are combinations of videos, canvas pages, and markdown files with easy-to-follow examples. The modules must be completed in order,  however, If a module contains familiar content, students can move forward to proceed with the quiz for that section.

Each course is designed such that students can study at their own pace. Students should be able to complete each course within four weeks, however, there's no implemented time limit within Canvas.


Upon successful completion of each course, students will be issued a statement of accomplishment. This includes a PDF badge that will be shared via email. Each badge serves as a statement of accomplishment, which can be presented in future courses to prevent retaking a bootcamp course.