After working as an engineer in the water industry for 14 years, Carolina Gonzalez realized her learning had plateaued and she was ready to pivot her career. She saw the potential of getting into the data science industry in Seattle, but her Python skills weren’t strong enough to get accepted into Metis, a local data science bootcamp. So Carolina chose to take the Metis part-time, live online, Beginner Python and Math for Data Science Course, to get ready for the rigorous Metis bootcamp application. Find out if Carolina got into Metis and what her plans are for the future!
Tell me about your education and career background before Metis.
My background is a blend of chemical engineering, a master's in Natural Gas Engineering and Management, an MBA and about 14 years of work experience. Most of my work experience is in the water industry at General Electric. I worked as a mechanical engineer, a process engineer, an applications engineer, and as a proposal manager.
How did you first get interested in data science?
I took some classes in business analysis at the University of Washington, and I started to get more interested in data science. I realized that there is big potential if you can analyze data and get some insights into what the data is telling you.
I was very comfortable in my job, but I felt I had plateaued in my learning. I still have 25 years or so left in my working career, so I decided to pivot. I find it very intellectually interesting working with data and turning insights from data into actionable decisions.
Since you’re based in Seattle, did you think about continuing at the University of Washington or teaching yourself data science rather than a bootcamp?
I had to figure out whether I could learn the skills without spending a long time going back to school. The classes at the University of Washington mostly taught R. I learned a lot from those classes, but I needed more project-based experience. I also felt that to make a career transition, I needed to build a portfolio of projects and things that I could talk about with employers.
Time is money, so if I was going to make a transition, I thought “the sooner that I make the transition, the more time I have to grow into this path.”
Did you consider any data science bootcamps other than Metis?
I looked into Galvanize and Metis. I had the opportunity to meet a couple of graduates from the Metis bootcamp. After talking with people from different backgrounds who went through Metis, they all convinced me that it was definitely worth it and spoke very highly of the experience and the instruction – so I started to lean more towards Metis.
I also had a couple of conversations with the Metis admissions team to talk about specifics such as the curriculum, and metrics – like how long it takes for students to get jobs.
What was the Metis application process like for you? Were you prepared for it?
I decided I wanted to go to the full-time data science bootcamp at Metis, but I realized that I needed to learn Python for the Metis admissions process. I started learning Python by myself, but decided to accelerate the process by taking the Metis Beginner Python and Math for Data Science Course.
What did you learn in the Beginner Python and Math for Data Science course?
The class is six weeks long; the first half teaches mostly Python, and the second half is math. We started with a very basic level of Python – using the Jupyter network, then looking at how to define different types of data and properties of data, along with some of the main functions and manipulations that you can do in Python. From there, we covered visualizations and different features and how to modify those for different types of charts. We also talked about Numpy, the use of arrays and Pandas.
The math portion covered linear algebra at the beginning, then very basic calculus, and probabilities and distributions. Even though I already had a math background, the Math curriculum was still a good refresher. I also did a lot of HackerRank exercises to get more familiar with the syntaxes, the code, the different errors, and to look at examples from the class.
What was the learning experience like during the Beginner course?
We had live online lectures twice a week on Mondays and Wednesdays, three hours each, from 6:30pm to 9:30pm Eastern Time. I had a chat window where we could post questions while the lecturer was teaching – that was very helpful. Another instructor monitored that chat window.
The instructors posted the Jupyter notebook for each day’s class and all the presentations on the class GitHub account. There was also a communication channel where we could connect over video and audio with instructors, other students, and see the code for each lesson.
When we learned the Pandas section, we were given a data set of NBA games; we had to use that dataset to answer a bunch of questions.
Did you think the Beginner Python and Math course was worth the time and money?
At the time, I was working full-time and I spent a significant amount of time per week on the course. But I think it was worth it. I learned Python a lot faster, and got an understanding of basic concepts a little bit easier. Having a stronger foundation made the full-time Metis bootcamp a bit easier.
If I hadn’t taken the beginner course, it would have taken me a lot longer and I probably wouldn't have been able to do the bootcamp in summer. I would’ve had to wait until fall or winter.
What were the other students like in your course?
We started with around 22 people. Some would attend live lectures, and some would watch the recordings. We would interact mostly through the class Slack channel – we could post questions, and sometimes have a conversation through that. There were students from New York, from the Midwest, Chicago, and Seattle.
Who were your instructors?
The course was designed by Metis Senior Data Scientist, Roberto Reif. There were two instructors. The main instructor was dedicated to the beginner classes – he was very good and very entertaining. The second instructor was on the chat answering questions, and would sometimes talk during a discussion about a specific topic.
What was the application and interview process like for Metis data science bootcamp? Did the Beginner course cover the questions that get asked in the application?
The beginner course materials were very helpful for the application. Part of the application is about Python and come from HackerRank challenges, and after going through the Beginner course, it was easier to answer those challenges. But the specific admissions questions per se were not covered in the class.
The first step of the application is through the Metis website. You talk about yourself and your experience. Then you do a little coding challenge on Python. If you hear back from Metis, they send you a link to complete a test within 48 hours. The first portion consists of questions related to math and Python challenges.
For the interview, I had to talk about a proposal for a project. There was also a question about probabilities and a discussion about the project’s proposed variables.
Now that you're in the full-time data science bootcamp, how prepared are you feeling compared to the other students who haven't taken the Beginner course?
Some of my classmates have a lot of their career experience in programming, which is an advantage. But there are other students who didn’t have that experience and might have benefited by learning more Python before the class. The first week or two were really difficult, but after that, I think everybody kind of got up to speed with Python.
What's your favorite project or assignment that you've worked on so far in the bootcamp?
We are in week five and working on projects. It's interesting looking at different problems that you would like to solve and figure out if you can find the data on how to structure the problem.
Hopefully, my favorite project will be the one that I'm submitting a proposal for today. As we learn more at Metis, I have more tools available for each project, so I think each project gets significantly more interesting. My proposal involves classifying startups as to whether they are likely to be acquired or go public. There are a lot of interesting problems out there, but finding the right data set is very important, and can be challenging. I think I have access to a data set now that will help me with my project, and I could complement it with other datasets and maybe web scraping.
So far, what’s been the biggest challenge in learning data science?
I think the hardest thing is dedicating the time to it. The good thing about the Metis bootcamp is that you’re putting everything else on hold and saying, "For this 12 weeks, this is what I'm going to do." But even then, there are other life responsibilities and things to balance. The more things you can take off your plate before starting the bootcamp, the more time you can spend actually working on your projects and the material.
Is there anything specific that you are doing to make sure that you have enough time to focus on the bootcamp?
I quit my job. That was one. Also, I organized my personal life differently. For example, at this time of the year, I sometimes go camping or do things like that, and I usually walk the dog in the evening. I've put off or delegated those activities to other people. I’ve shifted my activity system to make sure that I can dedicate the time to this.
What are your goals for the future, once you graduate from Metis?
Pursuing a career in data science! The main reason I'm doing this bootcamp is to work on data science projects.
I live in Seattle, so one of my priorities is to stay in Seattle – there’s a huge tech base here. I think there are a lot of interesting problems to solve beyond physical science, chemical or mechanical engineering.
What advice do you have for other people who are considering taking a data science bootcamp – should they take a prep course?
I would highly recommend taking a beginner or prep course. It’s an opportunity to not only learn the coding language that you will be working on, but also to get a taste of the material.
I also suggest talking with people who have already completed the bootcamp. On the last day of Metis, the graduating cohort gives presentations. When I was researching bootcamps, I went to those presentations and it was helpful to see the projects they could complete by the end of the program.