6th Annual Summer Institute in Statistics for Big Data (SISBID)

The Summer Institute for Statistics in Big Data (SISBID) is designed to introduce biologists, quantitative scientists, and statisticians to modern statistical techniques for the analysis of biological big data. Ali Shojaie serves as the Director of SISBID.

Registration

Registration will close three business days prior to the start of a course.

Session Dates: July 13-24, 2020

2020 Modules  |  Register  | Subscribe to Mailing List

  • Each module focuses on a different aspect of Big Data such as organizing and processing data for statistical analysis, visualizing data, or the challenges surrounding reproducible research.

  • Enroll in multiple modules to create an experience that best suits your interests.

  • Instructors are world-class faculty with expertise in all aspects of biological Big Data.

  • Participants receive a certificate of completion.

One of the goals of SISBID is to strengthen the statistical and genetic proficiency and career preparation of scholars from all backgrounds, especially those from groups historically underrepresented in STEM such as racial and ethnic minority groups, low income, first generation college students, veterans, and differently abled and 2SLGBTQ groups.

 

Cost Savings for 2020

The online format reduces our expenses and we are pleased to pass those savings along to you via lower registration fees for SISBID.
Group Early-Bird Fee per Module (Through June 22) Regular Fee per Module (After June 22) Payment with UW Budget Number
Academic, Government, Non-Profit
Regular: $575
Now: $375
Regular: $675
Now: $475
13% discount
Corporate, For-Profit Organizations
Regular: $675
Now: $475
Regular: $775
Now: $575
NA

Participant Comments

  • "This has been a transformative experience for me. Over the course of a few days, machine learning went from a fuzzy concept to something that I've already started applying to my own work in pediatric cancer and immunotherapy."
  • "The expert faculty did a wonderful job of presenting challenging and complex material with tools (such as R markdown) that allowed students of all different levels to learn and gain exposure to a rich set of tools and concepts."
  • "I gained skills that I can directly apply to my research. The labs and code were super helpful, and will aid me in my research projects."