I’ve learned how interdisciplinary data science is, and how a team of people with many different academic trajectories can work together on the same project, something that I don't think happens very often in other areas.

- Anonymous


I've gained a lot of valuable insight into the career fields of environmental health and epidemiology. I've also learned a lot about project workflow and how to work through the different phases of a long term project with a team. In addition, my skills in R coding and Tableau have improved a ton.

- Anonymous

John Taylor

My group has been focused on cybersecurity and automation methods to prevent and seek out attackers to keep Duke websites and accounts from being compromised. I have learned a lot about cybersecurity, a field that I otherwise might not have pursued. It has been a very interesting and enlightening experience so far and I am excited to continue learning from the Duke OIT staff.

Sydney Hunt

I have gained so much knowledge and confidence! And it is not limited to the area of technology, although I have learned to code in R, navigate PACE, and so much more. I have better discovered the benefit of working with a team and received motivation and mentors by seeing female-identifying students, like myself, succeed. Hearing their success stories via panels or team meetings has given me so much more confidence as a young woman wanting to pursue a career in STEM. I see that it is possible!

Albert Sun

Beyond solid technical machine learning skills, I've received a greater appreciation for data science as a tool to understand everything--from aircraft maintenance to the humanities. Before, I'd never expected that conducting humanities research would teach me how to wield and utilize the most cutting-edge research in machine learning and natural language processing. My team is using new package libraries and research papers written by lead researchers this year to conduct our analysis of ancient texts. In Data+, New meets Old.

Nathan Warren

Working remotely has made coordination much more difficult. However, we really have been embracing GitHub and box to overcome these challenges. I have learned a lot about RNNs and the applications of GRUs and LSTM's and how to implement such layers, in addition to learning how to use pytorch as previously I only used tensor flow.