Coreq: 18.02 or equivalent
Instructors: Professor Alan Edelman
Schedule: TR2:30-3:30, Labs TBA, virtual instruction
Provides a unifying introduction to computational thinking for technical and general-purpose applications. The class is intended to break down traditional walls between computation in science, engineering and computer science with applications from these disciplines. As an example, we will see how to apply differentiable programming to machine learning. The class uses Julia to provide students with a complementary programming language, with an emphasis on modifiable codes and performance. We assume no prior Julia experience, but we will build on Python from 6.0001. Preference for students who did well in 6.0001.