Using Interactive Notebooks and Open Data to Reproduce and Learn from Physics Discoveries

Students can be encouraged to think deeply about physics discoveries by engaging in research-quality analysis of data. In 8.316, Data Science for Physics, Professor Philip Harris uses open public data and Jupyter notebooks to enable students to delve into data from real physics experiments. From writing the software to select the data, to using computational methods such as neural networks, students are challenged to learn from Nobel-prize discoveries and to make new discoveries of their own.

Watch Philip Harris’ video here.