A Full Picture of How DS Relates to Other Fields

“The MSDS Program is a very rigorous program.” This thought has been embedded into our system even as early as the interview date. True enough, it met our expectations. There are tons of homework lined up and we must be competent in both written and verbal communications. We must always be on our feet, able to think quickly and critically.

I remember from the very start of this course, many people started reciting already. My classmates come from different educational backgrounds, different industries, different age groups… and there are just so many insights to pick up from them. My professors are all world-class who are not the typical academe-bred lecturers but those who have industry experiences as well. With the Introduction to Data Science course, it was easy to see the talents that everybody possesses because ideas being shared are stemming from personal experiences and are knowledge-based. It’s inspiring, and an opportunity to be a part of this program.

Along with the optimism came the acknowledgment that I have a lot of catching up to do. Majority of the people here come from technical backgrounds and are very skilled in communicating verbally and thinking on their feet. It was mentioned during the introductory course that to be an effective data scientist, we must not only be adept with programming but also be able to convey our ideas and communicate effectively with our stakeholders. Here, I got the general realization that at the end of the day, we should be acknowledging the synergy present when different departments and teams work together because the whole is greater than the sum of its parts.

Aside from the diversity of the group and the “soft skills” needed, I remember feeling in awe with how Data Science and Artificial Intelligence are already being implemented by many companies. Beyond the applications are knowing the background stories on what gave each company its competitive edge, how companies transformed their business models to make it data-driven, and the methodology and reasoning behind why they did such. An actual example will be Netflix and how they surpassed even their biggest competitor. It is good to follow the initiatives they undertook that led them to where they are now.

Further to the real-world applications, I also greatly value the exposure we got to the other components of data science such as AI Ethics, Data Privacy Act, and Data Strategy. It is good that even early on, we were not automatically submerged into the technical side of things. The MSDS program ensured that we get a full picture of how data science relates with other fields. It’s good that we are exposed to the business side of things, the legal side, and the human-centric side as well. I must say the MSDS program is turning out to be greater than expected. I look forward to our remaining months here.