Tell us a bit about yourself.
I started the Master of Information and Data Science (MIDS) program in fall 2015, and I'm currently in my third term. I have bachelor's and master's degrees in computer science, and I've spent over a decade working in the software industry. Most of that time I spent as a developer at Microsoft in the Windows server operating systems division. I built software for remote desktop technologies. I've taken a break from work to focus on my degree, and I'm really enjoying it so far. I have two little boys, ages 7 and 4, who keep me almost as busy as my course work!
At what school and in what concentration did you receive your undergraduate degree?
I received my undergrad in computer science from the Veermata Jijabai Technological Institute in Mumbai, India. I then received my master's degree in computer science from the University of North Texas in Denton, Texas.
Why did you choose the I School?
Data science seemed like a natural step for the evolution of my career, unlocking a whole new world of exciting problem solving and analytical work. And although there is no dearth of online courses on various topics related to data science, I realized there was enough to learn and absorb in this new field to warrant a systematic and fundamental-based approach — something only a degree could provide.
I was drawn to the datascience@berkeley program because of its broad and rigorous curriculum, covering everything from the basics to advanced topics in research design, statistics, and machine learning. Also, the ability to enroll part time was an important criterion for a working mom like me.
What is the I School's advantage?
The immersive online classroom experience with live video interactions, the professionalism and dedication of the professors, the supportive staff, the online Slack channels, and plenty of group work all make it feel like a real classroom experience. The part-time nature of the program is also a huge plus for busy working professionals.
What has been your favorite class at the I School and why?
My favorite course so far is the advanced course Machine Learning at Scale. It is a comprehensive treatment of applied machine learning at scale — so I've gone from bootstrapping my machine learning environment to designing and running machine learning algorithms with several gigabytes of data, and I'm only halfway through the course!
What are your future plans?
I am fascinated by machine learning and starting to understand how enormously impactful it can be. I would love to work in an area of research or application related to computer vision through machine learning. Eventually, I hope to be able to make a meaningful impact in a field that I care about — social, environmental, medical, education, or something similar.
Do you have any advice for aspiring information professionals/data scientists?
Data science is a very wide field; you can choose depth (e.g., a Ph.D. in statistics) or breadth. A curriculum like MIDS is a great "breadth" curriculum and, most importantly, prepares you for a career in the ever-changing landscape of data science.