It is my 6th week in the Data Science Immersive Program, and I’m still loving it. It is quite amazing how much we have covered over the last weeks, and even though it may seem like information overload some days, I am learning a lot and I am really happy with all the skills I am acquiring.

We have learned how to gather data when it is not readily available; how to clean data, engineer features, and prepare for Exploratory Data Analysis and Modeling. The Mathematics behind these algorithms are truly impressive, and even though I cannot claim — yet — that I completely understand every little aspect of it, the lessons are very helpful in giving conceptual understanding of how they work. Some of these models include Linear Regression, Logistic Regression, Multi-binomial Naive-Bayes, K-Nearest Neighbors, and Random Forest Classifier. Of course, this barely scratches the surface of it all, but it given amazing insight into the possibilities.

This and the previous week we started learning about Natural Language Processing, and it is so far one of my favorite subjects. Even though I have joined a very mathematical and code driven industry, the fact that I can analyze human language using these tools is very enticing to me, so I have been enjoying the material presented during the last two weeks even more than usual. Our third projects revolves around NLP and I have found it to be the most fun to work on out of all projects so far.

Among all the highly technical skills that I am acquiring, there are soft skills that I am learning or improving upon, which came as a surprise because I did not expect soft skills to be something that one might even need in Data Science. For example, I’m learning how to present to non-technical audiences in a way that is captivating and relevant to them. I’m learning about the importance of a good narrative when presenting insights and findings from my data analysis work. Presentation is a crucial part of being a great Data Scientist.

With almost half of the program behind me, I am starting to think about what will happen after it ends. I feel the capstone project nearing, and having to think of at least a couple problem statements to consider. I am also thinking about how much I will miss being part of the cohort, and seeing my classmates and instructors five days a week. It feels good to be part of this community of aspiring Data Scientists, where everybody is working really hard and giving it their best. As sad as I get about leaving sometime, I get very hopeful about what is to come after I complete this program, and I am very much looking forward to applying my new skills to do some good in this world. Finding a great job is on my mind, as the promising job market was part of what attracted me to Data Science, but most of all I realize just how many applications Data Science has and just how much I will be able to do in the future, whether it be paid work or volunteering for a good cause.

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