We have been getting a lot of interest in our upcoming deep learning course over the last couple of days. With applications closing today, we’ve heard from USF that they will be able to extend the application deadline. The revised deadline is October 17. This will mean some late nights from the team at USF to ensure that all enrollments are processed in time for the start of the course–so many thanks to them! USF’s page with logistical details about the course is available here.
We are also excited to announce an additional diversity fellowship. After learning about our decision to sponsor a diversity fellowship, USF has generously said that they will match us, by sponsoring a 2nd diversity fellowship for our course! Women, people of Color, and LGBTQ people are all invited to apply. To apply, please email [email protected] a copy of your resume, a sentence stating that you are interested in the diversity fellowship, and a paragraph describing the problem you want to use deep learning to solve. We are excited to start addressing the diversity crisis in Artificial Intelligence.
Finally, we’d like to announce that we have launched an International Fellowship program for up to five people, who will be able to fully participate in the course remotely, for free. We are very excited to introduce our first successful applicant, Samar Haider from Pakistan. Samar first taught himself machine learning using online resources like Andrew Ng’s Coursera class and is now a researcher applying natural language processing to his native language of Urdu, at the Center for Language Processing in Lahore. Pakistan has a rich heritage of 70 different spoken languages, many of which have not been well-studied. At fast.ai, this is exactly the type of project that we want to equip people to work on–domains outside of mainstream deep learning research, meaningful but low-resource areas, problems that smart people from a wide variety of backgrounds are passionate about. And Samar is exactly the kind of passionate person that we want to support–as well as teaching himself machine learning, he has even invested his own money to get access to GPU time on Amazon so that he can train models. We hope to see Samar’s fellowship benefit the Pakastani community more widely, by making available Urdu deep learning resources for the first time.
To apply to join Samar as an international fellow of the program, please email [email protected] a copy of your resume, a sentence stating that you are interested in the international fellowship, and a paragraph describing the problem you want to use deep learning to solve. The program is open to people anywhere in the world (including the US) who can not attend the course in person in SF.
International fellowship winners:
- Must be willing to attend the course via Skype in realtime, even if the time is inconvenient in their home time zone
- Must be willing to participate remotely with group members (who will be based in the San Francisco Bay Area)
- Will not be eligible to receive an official certificate.