I'm doing an MS in Computer Science at UT Austin!

Social Scientist -> Computer Scientist

As a person who conducts research in machine learning, I have always felt a little insecure about my background in computer science (CS). I have wondered if there would be a point when I am stuck on a concept and I would fundamentally struggle to overcome it. In my job, I work with many people who come from a background in CS or have received formal training in CS. I admire their understanding of algorithms and how to code efficiently.

In their past studies, many of them have taken courses in Data Structures & Algorithms and Object Oriented Programming. A solid background in these concepts usually result in conducting computational experiments more neatly and efficiently. Neat code is important for readability and reusability of prior work, which is essential for replication. Efficiency is important for optimizing the use of the resources you have at hand with time and hardware constraints. Unfortunately, these concepts are not taught in graduate programs in the social sciences. Therefore, if any social scientist is looking to transition to a career in this area, they will have to play catch up.

Of course, a graduate degree is not necessary to learn this. I would even venture to say a degree is not necessary. There are many options to get this training, which includes books and MOOCs. So why am I pursuing a master’s then? Well, there is a lack of directed instruction for remote and part-time learners on the theory behind machine learning that’s suitable to pursue a research path.

The Program

UT Austin Department of Computer Science

Although 2020 has been a less than stellar year to say the least, I am very hopeful about what 2021 will bring! I am particularly excited that I have been accepted into the Master of Science in Computer Science at The University of Texas at Austin for spring 2021.

Snippet of UT Austin Admission Letter

The Department of Computer Science at UT Austin is a top ten computer science department in the US. It also ranks in the top ten for the subfields of Artificial Intelligence and Machine Learning. The professors presenting the coursework are some of the best and well-respected computer scientists in the world.

Compared to competing programs, such as Georgia Tech’s online MS in CS, the focus of this program seems to be to provide a mathematically-rigorous and theoretical exposure to machine learning. This is evidenced by the inclusion of mathematics courses in the program. This unique aspect of the program is primarily why I was interested in pursuing it.

To be granted the degree, you must complete 30 credits/ten courses that include at least one course from each of the three areas of Theory, Systems, and Applications. Upon completion, I plan to have taken the following courses:

  • Graduate Algorithms
  • Optimization Theory
  • Online Learning and Optimization
  • Advanced Linear Algebra for Computation
  • Machine Learning
  • Deep Learning
  • Natural Language Processing
  • Reinforcement Learning: Theory and Applications
  • Parallel Systems
  • Quantum Computing (or substitute with theory-based ML course at Stanford)

The program does not include a thesis, which is something I am very happy with. I have written my fair share of theses between my bachelor’s, master’s, and doctorate programs. I plan to join one of UT Austin’s ML research groups (assuming remote students are allowed) and will leverage my existing research skills to work on projects. In my case, I believe there are more advantages to this path than writing another thesis.

Plans for the Future

As I am transitioning to having a more research-focused career, I believe this qualification will gain me more credibility in the area of computer science. I have strong programming skills and a solid understanding of machine learning and its applications, however it is difficult to signal that to those who haven’t worked with me or know my background in depth. In fact, there are many companies who screen candidates on whether they have a degree in computer science or not. Having this qualification will not only further build credibility inside my current company, but also in any future role that I plan to pursue. I’m excited for this next step in my career!

In the meantime, I am working on a special project with a good friend of mine that will be launched soon! We are both researchers and the pandemic has sparked a creative and entrepreneurial spirit in us. We hope to launch this project by the end of January 2021, so keep an eye out here!

Ancil Crayton
Senior Research Scientist

My research interests lie at the intersection of machine learning, economic analysis, and public policy.