Summarizing my speech at WomenTech Network 2020 on “how can get started with Data Science — sharing some tips and sources and, my journey from being a humanities student to getting a Master’s in Data Analytics.

Starting off by explaining what is data science:

There are numerous definitions of Data Science, some people might say its computer programs do really cool stuff. Or, data wizards would define data science as doing magical stuff with data!Or there are people who like to define it as an human-computer relationship: they might see — Data Science as “converting human problems, putting them in a computer — thus, making it a computer problem, and expecting the computer to solve that original human problem.”

Here, we are essentially making our problem, placing it across and making it someone else’s problem to solve.My story: From Humanities to Data Science:

When I moved from India in 2015, I started off as an economics and international studies student. But, in my sophomore year as a part of my curriculum I had to take a class in Information systems and statistics. Through these classes I accumulated the knowledge of how we can use MS access, MS excel and statistical tools like regression in the real world. I got genuinely interested in information systems and decided to major in that too.

Studying three very different subjects was a hassle initially, but I am glad I did that. Through information systems I realized that _I undoubtedly enjoyed understanding the world through numbers and mainly through trends.

_By the end of my bachelors, I knew I wanted to get into the data and information systems field. But, at that time I was not completely comfortable with analytics and definitely lacked working knowledge and needed improvements in data science. So I decided that the best way to improve my skills was to go back to Grad school. (There are other ways to improve your Data Science skills, some of those are mentioned towards the end of this article). But, I decided to apply to the Business data analytics program at Loyola University (it is the best MSBDA program in the Chicago land area and ranked the 33rd best in the country, so it instantly felt right.).

This program basically prepared me for working with statistics in Excel, how data can be employed in marketing and supply chain (that domain knowledge really helps in making sense of all the number crunching that you are doing). Along with that, one thing that I really appreciate about this program is the curriculum’s overall emphasis on hands-on experience to learn different machine learning approaches. So, since the last 8–9 months I have been intensely involved with 6 different projects, some of them are with actual companies and involve aiding them with solutions to a business problem that they are facing. And, for some I had the flexibility to work in the area I was interested in and was able to choose a dataset on my own and build models that I identified would be the most impactful to solve the problem.

#data-science #machine-learning