SDS Bootcamp Courses

About The SDS Bootcamp Courses

A solid foundation in statistics, Python, 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 three 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 Fall 2021 SDS Bootcamps as of August 2nd, 2021. Students currently enrolled in the Fall 2021 sections must complete the bootcamp by Tuesday, December 7, 2021.  


Course Descriptions

Introduction to Python For Data Science

A self-paced introduction to the basics of programming in Python 3. This course is organized as a series of modules covering Python variables, expressions, statements, including loops and iterations, functions, and pandas library for reading and manipulating data sets.

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.


How To Register

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

Register Here


Taking Each Course & Time Requirements

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.


Course Completion

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.