Data Science and Artificial Intelligence

Talking robots are a thing of the past. Today, we want self-learning robots who can both be our calculator and our friend. The course Data Science and Artificial Intelligence showed us how to take the first baby step into the new and upcoming field. So my batch was the first to experience this course and it was one of a kind!

The beginnings of this course were confusing and hazy where I felt like I was being blindly led through a dark tunnel. At one point I was collecting and cleaning data and at the next I was interpreting a regression graph, I wasn't able to connect the dots until a very informative meeting with the professor taking the subject. He showed me YouTube videos on the advancements of AI to give me a bigger picture and then narrowed it down to show me where I stand in that picture. He explained the intention behind each topic taught and how they would eventually connect together to form a part of the big picture. That 45-minute long meeting helped me piece together the concepts very clearly and intuitively.

The course was conducted completely in Python, something I had experience with from the previous semester. So I was able to manage the coding part after some practice as well.

There was another very large "mini-project" in this course as well(just like in ICT). Only this time, we had to do more than just recommend canteens, we had to do something that could really be used in reality. The problem? We didn't have a problem statement. The professor handed us a website link and 3 datasets to choose from, and asked us to make our own question. Also the groups were also randomly allocated to us, which meant that I would have to work with people who I had never seen before and could potentially be unhelpful freeloaders.

But as luck shines in unexpected places, I was placed in the best team I could ever hope for. My group members were the most proactive and hard-working people I had ever seen in university, and it was a pleasure working with them. It's only no wonder we ended up taking all future classes together so that we could team up for projects again.

Back to the "large" mini project. The first few weeks of the allocated time of the project went in deciding the question and reviewing it with the professor. After that, we then started on the coding. We decided to do a happiness index prediction model and analyse with interactive graphs. After a lot of hard work, we were able to make the model and get average prediction results as well. Presenting the project was also a good experience for me since I was clear on our work and the concepts we used, I was able to present without a hitch.

This course was the major factor why I decided to do my URECA project in year 2 on deep learning. DSAI was a course that opened to me the doors to a whole new world and I'm beyond excited to see what lies in store for me there!