Deep Learning Certificate Part I
Part I of the Certificate in Deep Learning, taught by Distinguished Scholar Jeremy Howard and Professor Yannet Interian, aims to make deep learning accessible to the widest capable audience. The goal of this seven-week, 100% in-person program is to provide a rich understanding of the foundations, applications, and future directions of deep learning. This knowledge will allow participants to build new deep learning models, apply and fine-tune pre-trained models, and develop, implement, and test new algorithms and architectures.
Suggested prerequisites or prior experience include one of the following:
- 1+ years working in a coding-based position
- 2+ years studying computer science at the university level
- completion of a data science or programming boot camp plus 6+ months work experience
- significant open source coding experience for 1+ years
- Linear Algebra: matrix product, matrix inverse, orthogonal matrices
- Calculus: basic differentiation and the chain rule
|Location||101 Howard St.
San Francisco, CA
|Continuing Education Units||1.5|
$1125 for USF current students and alumni