In this course, students learn data science fundamentals that are more in tune with their applications to business; essentially, how the field is applied in the real-world. Students are provided with a comprehensive overview of data science and …
I now realize that a true data scientist is one who is in the middle of the action, someone who ties together the different aspects of a problem, whether it be the business side, finance, technical, or even HR side of things; and after taking all of these into consideration, aims to solve a problem using a data-driven approach. These, to me, are radically different notions: the notion of simply outputting data that will “magically” solve a problem, versus realizing that we are first and foremostproblem solvers, whose main weapon and tool is the data driven approach that we bring into the fray. And I hope that the next batch would find this as exciting and as fulfilling as I do now.
One must not also forget that all of these data-driven initiatives have potential impact on the client, and to society in general. Most data scientists are too excited about the potential benefits of the project, that they fail to think about the risks on data privacy and other ethical issues. If these issues are not addressed, the project will also fail, no matter how revolutionary it is.
A student of the MSDS program must always remember this... that despite their proficiency in the classroom, innate business acumen, daily immense pressure, and tantamount workload, it is people’s lives that we are analyzing, it is an organization’s future that we are augmenting, and it is a society that we are drawing impact for – data science is a powerful tool that draws impact that many have not yet realized.
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.
Personally, this course has managed to set my expectations for my career as a data scientist. It is both a ride on a rough road and a slide on slippery ice and that I need to remind myself that data science is the car to cross the rainbow and not the actual pot of gold.
IDS gave me not just an overview of this big umbrella of data science. It has also set my expectations on what will my role be after the program. That I am not just a programmer, an analyst, mathematician, statistician, physicist, I’m not going to be just creating the model. I will have to be holistically prepared to do everything.
One must not also forget that all of these data-driven initiatives have potential impact on the client, and to society in general. Most data scientists are too excited about the potential benefits of the project, that they fail to think about the risks on data privacy and other ethical issues. If these issues are not addressed, the project will also fail, no matter how revolutionary it is.
For someone who is a novice and comes from a background that is far from data science, this course was an eye-opener. Of course, at the onset I already had some knowledge about the potentials of data science, but I never realized that there are a lot of real-world applications for this new field. One of the main reasons why I took this course even at a relatively advanced age (compared to the other students) is that I wanted to change an industry that should be data driven but as of the moment was more reliant on traditional analytics. I am not saying that this is wrong, but a lot of real estate industry professionals are still relying more on experience compared to actual data when making business decisions. I observed that in other countries, there is a wealth of data about everything related to real property transactions, I found it unsettling that in the Philippines there is relatively no data available to base decisions from.
I like how data science was presented as a tool to answer business objectives and not as the next big thing which is what seems to be happening now. As a management major, the lesson that everything a company does should be geared towards the company’s VMO is always emphasized. Anything that does not help the company towards achieving its goal is a waste of resource.