Self-Driving Engineer

from University of California, Berkeley

The Best Courses for Self-Driving Engineer at University of California, Berkeley

Updated October 2022

Course Importance and Why
CS 182 Importance: 3.5 / 5.0
  • A hard class to be sure but gives a surprising amount of exposure into the current state-of-the-art (especially transformers, which are leveraged in most detection applications in self-driving vision pipelines) - Steve, class of 2022
  • Aside from the grad level cs280, this is probably the best (academic-setting) exposure you'll get to the architectures/paradigms that are in use in the self-driving stack at companies like Tesla, Nuro, Mobileye. - Steve, class of 2022
CS 189 Importance: 3.0 / 5.0
  • Cal's canonical ML class - Steve, class of 2022

Helpful Tips

Updated October 2022

  • There's a lot of work being done on state-of-the-art in Self-Driving / Computer Vision at Berkeley AI Research (BAIR). Look through the list of professors/grad students and shoot them an email if you're interested in joining their research! - Sid, UC Berkeley, PlusAI

Notes from the Field

"Check out this site's UC Berkeley guide for ML engineer, there's a fair amount of overlap."

- Sid, UC Berkeley, PlusAI

Opportunities

Coming soon.