“Having no prior exposure, outside of a statistics course, to data science and data visualization, I feel like I got a lot out of this program. At least for me, there was a little bit of "drinking from a firehose,” and a steep learning curve but I learned a lot very quickly. The data visualization programs with which I worked are definitely ones I could see myself using in the future.”
—Anonymous student
Remembering the Middle Passage
“This summer of Data+ showed me that data science research is also interested in intensely analyzing and understanding outliers of a dataset, rather than just the averages. Many probability and statistics classes emphasize the mean, variation, and overall distribution of a dataset without paying too much attention to the outliers and asking if those outliers can really be explained by the same set of processes affecting 99%+ of the other data points. This summer of Data+ showed me that data science research is also interested in intensely analyzing and understanding these outliers.”
“I feel I have gained a much greater understanding of how to approach problems computationally as well as working on a small team in order to solve/fix these problems! It has been a great experience overall, and I wish I could do it again. Working with the stakeholders we had was great, because they were also so involved and enthusiastic. Our project manager couldn't have been better either. I had a great summer with Data+!
“Data+ in many ways widened my perception of what it means to participate in Data Science research. My particular project was pretty in line with my perception before coming to Data+ but many of the other projects looked very different than I imagined a Data Science research project looking in terms of the type of data they were using and the clients.”
—Ryan Culhane
Speech Emotion Analysis
“I didn't know Data Science research was a thing at the undergraduate level, so it showed me some possibilities. I have gained a better understanding of machine learning topics and when to apply different methods. I've also learned a lot looking at results from our models and pulling meaning out of them–even if that meaning is just that there was a bug and we need to redo it differently.”
—Varun Nair
“I gained valuable experience with working both with data, something I had never had the chance to do before, but perhaps more importantly I gained insight into working with a small team alongside a project manager.”
—Dennis Harssch
Big Data for Reproductive Health (Year 2)
“I think that Data+ has taught me a lot about how to create something really cool out of nothing. We had to change our project goals because of technical issues and holdups, and I think I learned a lot about how to go from just raw data and ask really interesting questions.”
—Aidan Fitzsimons
Recidivism in Durham County Jails
“I now understand there are many ways to be useful in a collaborative environment. As the only non-technical major on my team, I first believed I couldn't bring as much to the table, but I found there is immense utility in being the person with the least technical experience. Not only was I able to perceive problems in a different way, offering fresh solutions, but I was also able to gain much more knowledge from my teammates. Additionally, I was able to incorporate my sociological understanding of people into the design aspect of our project to create a truly useful user experience.
“The most important thing I've gained this summer is a sense of understanding of what it's like to work for a client and produce deliverables on a timeline. The biggest takeaway I've gotten about data science is how much data is missing in the world, and how hard it can be to find. There are a lot of really beautiful, well formatted datasets out there, but sometimes, there just isn't a way to get what you're looking for--and that's often where you come in.
“I feel like I gained a lot of hard skills related to coding in different languages like Python and R. I'm really happy I had a chance to dive into some more complex machine learning problems like computer vision. Most importantly, I feel like I've gained enough confidence in my data science skills to pursue a related career after college.
—Niyaz Nurbhasha
Basketball Analytics Pipeline
