Hi, I’m Brian Liu, and I’m a junior double majoring in 6-14 (Computer science, economics, and data) and 18 (Mathematics) and minoring in music. This past IAP, I worked at The Coding School as a curriculum development and data analysis intern. The Coding School is an education non-profit aiming to deliver effective programs in STEM for people from all backgrounds, including initiatives in quantum computing, artificial intelligence, and big data.
Having come from a background in STEM, I know firsthand that the field can be intimidating and exclusive from a young age. That was a major factor in my decision to take on projects in data analysis and curriculum development because I wanted to make opportunities in quantum computing and machine learning equitable. There are many ways to tackle inequality, and I felt like my data analytics skills could be utilized to provide insights on both admission and program well-being. Using python, airtable, and qualtrics, I assembled a report on survey data from two of TCS’s flagship programs, Qubit x Qubit and trAIn (quantum and AI programs, respectively). The report included both statistics and visualizations which I presented to the program managers at TCS.
Since people of color are underrepresented in STEM fields, I hope my work in data analysis at TCS will be able to provide insight on how to improve the equity of education at the company’s program and subsequently society as a whole. I was able to use analytical methods to show which groups were most likely to drop out or struggle in TCS programs, and suggest effective practices for encouraging and aiding their study through survey data. TCS is a bridge between higher education in exciting broadening fields such as quantum computing, so making sure that the underrepresented students TCS sponsors succeed is amazing to see.
My other project was aiding the curriculum development for the machine learning student and professional development programs. I was onboarded into TCS at a very exciting time since it was the start of both the AWS professional development and Microsoft quantum initiatives. Seeing how passionate a lot of the full-time employees were motivated me to work towards my goals and accomplish as much as I could in the short time span of January. I was able to work and complete a lab on KNN, k-nearest neighbors, a machine learning algorithm used for classification that will be used in the year long course curriculum for the trAIn program.
My philosophy throughout college has been to explore possible paths for my life after college, ranging from research to industry to now startups. My internship helped me explore my tentatively chosen career path, and it was a wonderful experience being able to immerse myself in startup culture. It’s fast paced, with short timelines and quick turnarounds. It’s also tight-knit—everyone is friendly and familiar. Although my internship was remote, I was able to meet up with a few interns and supervisors at the
WeWork in Cambridge. Seeing everyone in person was great, and it’s refreshing to see the real people behind zoom screens.
I am sincerely thankful for the opportunity to intern at such a dynamic and impactful organization. I’ve learned so much, from working independently and remotely to new coding languages and databases to communication channels at startups. I am hopeful that my work will positively affect the education sphere and provide opportunity to people from all walks of life.