Memorable Things I Learned from IDS
- Beyond the lectures, IDS is full of real talk. It dangled the carrot, while also telling us the hell hole that we have to go through to become an effective and competent data science leader.
- The course has given me an overview of what data science is—and what data scientists are doing out in the real world. It’s not just about being obsessed over data, but on how you are going to use it to answer a business question.
- Leading the data science revolution is an undertaking usually left for the techy guys to do. This is the reason why most data projects don’t get to scale. The C-level executives need to work hand in hand with their technical people to really find a common ground and write a well-rounded data strategy for the company.
- It has exposed me to the deep vocabulary of data science, making me more conversant in the field. But this is not just about all the buzzwords of data science. It means being able to talk to a wide variety of individuals—novice, generalist, specialist, manager, and executives.
- It also taught me to be more critical, analytical, and creative. Remember the data map of Facebook connections? It taught me of how to be intuitive and see things differently. A good data scientists can extract meaningful and actional insights even from things most people in the company are not able to see.
- As the cliché goes for, garbage in, garbage out. Without a clear end in mind, feeding in the wrong data will lead to imprecise output given by our algorithms. There is so much focus on training data, but there is little attention given to the very problem we are trying to solve. It has to begin with a question that needs answer.
- What I liked most about the course is its practitioner-oriented approach. Different experts in the field were invited as our guest lecturers, and they all shared their real-world experience of what doing data science is like. Stephanie Sy of Thinking Machines pretty much gave us a picture of how flexible the work of data scientists are—you have to fill in for roles of data engineers, salesperson, marketers, communicators, among others. Data scientists are called unicorns for a reason!
- Exposure, exposure, exposure. I Think it’s so cool how we are asked to be out in the field at the early stage of the school year. This brings us real-world exposure to actual companies that are trying to address actual industry problems.
- Side notes are as good as the main course. Prof. E usually gives tips and examples from big companies she worked with. This is really helpful in our final project presentation, and of course, in our capstone as well.
- Learning springs from everyone. Being in the same class with all these experienced brilliant people, you can learn from them so much when they share their experience from their past or current companies.
This essay was a requirement under the IDS class and has been published with permission from the author, one of my MSDS students. - Prof. E