I’ve already added a little bit about myself in the ABOUT section of the blog, so for my first entry, I want to talk a bit more about why I joined Metis, and why this blog exists. If anything, this first blog post might be helpful for people thinking about joining Metis or a similar Data Science bootcamp.

As its website states, Metis’ mission is to accelerate the careers of Data Scientists by providing bootcamps, part-time professional development courses, online resources, and corporate programs. Metis’ Data Science bootcamp is accredited, full-time, and immersive. For 12 weeks, you receive extensive in-person instruction and personalized support from a team of Senior Data Scientists and Data Scientist TAs.

I chose Metis for several reasons. (1) I highly valued Metis’ curriculum and model, as it not only provides the technical skills needed to become a Data Scientist, but it also pushes its students to build a portfolio, create an online presence, and polish their communication skills. (2) I liked my first impression of them. Staff were friendly, welcoming, and always available to answer my questions. I went to a couple of their open houses, and I just liked the Metis vibe. The students and alumni I met all seemed to be on the kind of trajectory I’d like to follow. Most also confirmed that they had been in my place at some point: tired of teaching themselves and ready for someone to help them grow. I really liked their website too (although I know they’ve change it now). (3) I liked that they are accredited. (4) Metis offers a $3,000 scholarship for women, minorities, and, in a couple of their campuses, for members of the LGBT community. Now, full disclosure, I am a gender nonconforming Mexican woman and lesbian, so of course I loved that. But despite any personal benefit, any program that offers special considerations to underrepresented groups gets extra points in my book.

I did have a couple of concerns about joining Metis. The first was just knowing if I was ready. I had taken some formal university classes on statistics, but coding was something I picked up on my own through online classes (Udacity, Codeacademy, Learn Python the Hard Way, etc). However, Metis staff encouraged me to apply with the promise that if I did not meet the minimal requirements, they would provide feedback so that I could apply next time around, at no penalty. The other concern I had with Metis is that it focuses solely on Python and does not include any R (for the non-data scientists out there, Python and R are both programming languages popular with Data Scientists. You can learn about the debate between these two languages by Googling and reading the zillions of articles and opinions.) Ultimately, I decided that learning one language really well was enough of a challenge and that I could later focus on learning others.

Once I decided to apply, the process was pretty quick and it goes as follows: First, you complete an online application which includes a self assessment of programming and statistical skills, a stats question, a small programming challenge, and a couple of open ended questions so that you have a chance to introduce yourself and your goals. Soon after, you hear back from the admissions department, and you set up some time for a 48-hour challenge which is composed of some calculus, math, and stats questions; a bit of python programming; playing with an API; and a creativity portion in which you communicate a potential passion project. Once that is done, and if you successfully submit everything in the allotted timeframe, there is an interview. The interview is composed of general questions as well as a review of the challenge.

To give you an idea of how quickly things move, I went through the process at the end of November 2016, and I am now part of the Winter 2017 cohort, which started on January 9th.

I do want to say that I understand that attending a boot camp is only the beginning of a career related to Data Science. However, my hope is that the skills I will learn at the Metis boot camp, coupled with my background, will render me a strong candidate for the future. I have worked and taught myself the basics of Data Science, and I now look forward to taking a leap forward.

So, that is how I ended up at Metis, starting a Data Science blog. One final thought I wish to add is that I am not a natural writer (English isn’t my first language) and, consequently, not a natural blogger. I’ve never really felt that I had something to say that other people would be interested in reading. However, I do believe one learns the most when taken out of their comfort zone. So bear with me while I find my voice and overthink what I should or should not include. Here we go…