Computer Science

The fifth month of the Lambda School program is a unit on Computer Science. This was probably the most difficult part of the program for me, because the daily assignments put so much emphasis on the speed the code could run, and I still am not the most efficient writter of code. It was still a good experience, since this covered the basics of coding and important ideas behind how code works. I had always thought it was strange that the program throws you straight into your track without any introduction to coding, but I can say that it works! Regardless, the fifth month was honestly a haze of very similar days with a lecture, then a coding assignment through Codesignal. This repetition was certainly tedious, and I am glad that it was put toward the end of the program, because that was honestly the most boring month of the program, even if the content was actually very imporatant.

Labs

The final month of the program, I was working on a project with three other data scientist and three web developers. We were assigned a project with the non-profit organization Human Rights First (HRF). We started a greenfield project to provide HRF with a system to help asylum lawyers find cases similar to ones they are working on. To do this, the data scientists first had to convert .PDF files to plain text so that we could perform Natural Language Processing (NLP) techniques on them. The main goals that my team had in the month that we were working on the project were: find a way to pull the immigration judge from the documents, and find a way to pull the specific court from the documents. We also wanted to work on finding a way to pull information about the arguments made in the case, finding a way to pull the country of origin from the documents, and finding a way to pull the acutal outcome of the case from the documents. Unfortunately, we were unable to meet the stretch goals, and barely met the goals for the minimal viable product (MVP). Fortunately, the stakeholders loved what we had done, and are looking forward to what the future Lambda School Labs groups can do to improve the groundwork we helped to lay. The code for this project can be accessed here

Reflection on Lambda and My Future

Now that I have graduated from Lambda School, it’s time for me to start my job search. This may be the most difficult part of my career as a data scientist so far, but I am hopeful that it won’t take too long for me to truly begin my career. It’s still crazy to me that six months ago, I had only ever written basic print statements, but now I can write code to have my computer read and imitate Shakespeare, or tell me if I have a picture of a cat! I can even get my computer to provide recomendations to someone! I know that I still have a lot to learn when it comes to data science, but Lambda School has certainly provided me with a solid foundation, and I can’t wait to see where I go next!