Big Data Summer Program

Program description:

The Big Data Summer Program hopes to empower students to conduct data analysis and learn research process in health and social science fields. With the guidance of near-peer mentors, the students will work in collaborative teams to learn how to program in R, and then apply their skills to an original research project.

The program is divided into three parts. During the first 6-weeks student will learn programming skills in R through online classes and by reading materials and resource provided by the instructors. Students will work in groups and serve as a resource for each other to discuss questions and issues that come up. There will also be a weekly meeting with the instructor or near-peer to provide a deeper understanding of the learning material. Then you will be assigned to a scientific research project to apply and practice the analytic skills for 2 weeks. The last week participants are required to present their results to peers, mentors, and instructors at the SFSU summer research colloquium.


·      Build concrete data science skills with the support of peers

·      Gain experience in conducting research

·      Network with professors

·      Enhance skills to be a (paid) research assistant

Eligibility and selection criteria:

All undergraduate students are welcome to apply. Successful candidates will be self-starters, helpful peers and have interests in health and social mobility questions.

Program requirement:

·      Dedicate time and energy to learning a statistical programming language

·      Have strong interests in health and social mobility questions

·      Commit 9-10 hours per week for 9 weeks from June 3rd to August 3rd

·      Have availability to meet on campus regularly over the summer 


Important dates and deadlines:

Application Period: Friday, March 1, 2019-Sunday, March 31, 2019

3rd week in April: Notification of decision

June 3rd: Program Starts

August 3rd : Summer Research Symposium

If you have any questions, please contact Bobby Chakalov at

The application process and detailed information can be found here.