Below, Prof. Rama Ramakrishnan describes what students gained from taking 15.773 Hands-On Deep Learning.
After teaching the course several times now, one of the most gratifying pieces of feedback I’ve received comes from students who either didn’t have a technical background or had one that was many years in their past. They weren’t at all sure they had what it takes to build a model with their own hands. Many of them have told me that this course gave them the confidence (or in some cases gave them back the confidence) that they can actually do it themselves. That means a lot to me. I’ve always felt there are lots of smart, curious, hardworking people who simply didn’t have the benefit of the right technical background. This course makes it possible for them to access deep learning and, more importantly, use it in a hands-on way to create valuable new things.
An unexpected source of positive feedback has been from students who had already taken a mathematically oriented deep learning course and still took this one. They told me they understood things on an intuitive basis for the first time, even though they believed that they had already mastered the mathematics of the material! That really validates the design philosophy of the course.
