Graduate student at Harvard University
What are you doing right now?
I am a Computer Science graduate. After graduation, I joined the Indian Institute of Science as a Research Associate and worked there for two years. I’m an incoming graduate student at Harvard and am currently working with the Univ team as a Research and Teaching Fellow
Area of interest
Artificial intelligence and sustainable computation are the areas of my interest.
Why did you first sign up with Univ.AI?
I came across Univ.AI’s AI Foundation Program while working as a research associate at the Indian Institute of Science. I joined immediately as I was working on a few projects that required ML knowledge and thought it would be a great opportunity to hone my skills. Additionally, the opportunity of learning from Harvard and UCLA professors was pretty exciting.
What role has Univ.AI played in your learning journey in Data Science and AI?
I had prior knowledge of ML, enough to apply it for basic applications. However, my knowledge was very fragmented. I could handle the coding but I didn’t have a solid understanding of why one algorithm worked better than another for a given application. The Univ.AI Foundation course gave me a structured learning environment. They helped me understand the theory behind why something works when it does. I can now say that for me, this is one of the most important things there is to learn in machine learning.
If you had to share just one thing that you learned in the course, what would it be?
Attending summer school was an extremely enriching experience. If I had to point out just one aspect of what I loved - it would be the learning environment. The style of teaching was very engaging and something that I had not experienced before. I was used to the usual theoretical book style teaching and not the application-oriented style. The professors went out of their way to create an interactive experience.
What surprised you about the course?
The quality of peer group and the personalized time devotion by the professors are the two things that surprised me the most because I wasn't expecting the professors to personally talk to me about career decisions and any other problems I might be facing in the teaching process.
Have you seen new opportunities as a result of the course? Do you feel better equipped for new opportunities?
The experience in itself was rewarding. Post Univ.AI, I started to love working with machine learning. I attribute this to the knowledge I gained in summer school. I could confidently address drawbacks in current literature related to data science and machine learning, through well-informed research. This has proved to be phenomenal in my growth as a researcher as well.
What advice would you give to a new Univ.AI student?
You will learn a lot regardless, so enjoy the experience. The connections you make with your peers will help, so try to meaningfully interact as much as you can. Also,the courses are designed to encourage independent thinking, so don’t shy away from asking stupid questions. Try to think out of the box, this is highly encouraged during the course. Make sure you completely utilize your time with the professors, it is not only stimulating but also outright fun!
Any final thoughts or recommendations about the course?
The whole experience was so wonderful that I just had to keep in touch with Univ.AI. I was inspired by their vision. This is the first of its kind, a platform that provides live course instruction. Honestly, I am not someone who has been able to stay motivated enough to complete courses on other websites, I think I needed a little more incentive. which is true for many, I presume. Through live classes, personal doubt clearing sessions, and fun competitions - the Univ.AI method works and makes you stick till the end.