Photo by Tim Gouw on Unsplash
For the last year, I have been a Senior Data Scientist here at Metis, where we focus on data science training, including a 12-week immersive bootcamp program that helps individuals transition into data science careers. Below, I answer the most frequently asked questions that I get from individuals interested in our bootcamp.
I'm thinking about applying to the bootcamp. What should I do next?
Apply! There are three parts to the admission process: an online application, a technical assessment, and a video interview.
Among other skills (such as communication, curiosity, passion, and grit), we look for applicants who have technical skills in Python, Linear Algebra, Calculus, Probability, and Statistics.
I would encourage you to apply now because at each of the three stages of the admission process, we review your application and determine your preparedness to succeed in the bootcamp. We either advance your application – or if we are unable to do that – we will let you know what skills to focus on as you study so you can re-apply in the future.
Why does Metis have prerequisites?
The bootcamp advances at a fast pace and many of the covered pre-req concepts are fundamental. Additionally, Metis is not incentivized to push you through the program if you are not fully prepared. As the only accredited Data Science Bootcamp, we must meet the standard of our independent accreditor (ACCET) in maintaining at least a 70% placement rate for our alumni.
This distinct level of accountability means that we really want you to be totally prepared for the program. As you'll come to learn, every element of our structure and support is geared towards making sure you're prepared and that you are set up for a successful transition into the data science industry.
It has been years since I learned Calculus, Probability, etc. How do I brush up on those skills?
We offer Metis Admissions Prep on our website, which provides self-study resources in the technical content areas we assess during the application. This allows you to explore one or more topics at your own pace.
We also offer a structured Live Online course called Beginner Python and Math for Data Science. This course was built for true beginners to data science and covers fundamental Python and math concepts needed to start your journey. In the Live Online format, you have the option to collaborate directly with your instructor and peers during lectures, office hours, and via the course Slack channel. I co-designed this course, and you can learn more about it by reading a Q&A blog post with my colleague Gordon Dri, the other course designer.
What types of jobs can I expect to get after the bootcamp?
Data science is a fairly new field and covers a wide range of topics. Every data science team should have members that cover business, science, and engineering.
These can be further broken down into the following skills:
Business: Communication, Storytelling, and Subject Matter Expertise
Scientific: Modeling, Statistics
Engineering: Data Munging, Software Engineering
It is important to highlight that there is no one single person who has all these skills. Our alumni take roles in each of these areas.
Those who take business roles are individuals who can connect well with non-technical folks (such as managers, key stakeholders, and/or potential customers) and translate the business requirements into technical tasks. These individuals can also communicate with the technical folks and understand the challenges and limitations of the different projects, algorithms, etc. They also excel at project management, scoping, and have strong people skills.
The individuals who take scientific roles end up building or using models, creating and testing the different hypothesis, are proficient with programming languages such as Python and R and can build quick prototypes and iterate on them. They focus on finding insights and try to improve upon the old ways of doing things.
Finally, the individuals who take on engineering roles tend to work on production quality code in languages such as C#, write test cases, manage and organize databases, ensure data quality, and more.
Larger companies tend to have these three areas distinctly separate, while they are not as clear at smaller and medium-sized companies. I purposely am not using job titles because I have seen the same title mean very different things at different companies.
If you want to learn more about how Metis can help you get hired in data science, check out this post.
What advice do you have for someone who is about to start the bootcamp?
“…you can’t pour from an empty cup…”
This is life advice. If you are not feeling well, you will not be able to learn, enjoy life, and take advantage of the bootcamp. Your optimum learning state is when you are relaxed and having fun. On occasion, I have seen students so stressed out that they struggle to pay attention during lectures or can’t focus on simple tasks in their projects.
So, how do we get into an optimum learning state? The answer is what we already know: eat well, sleep well, and exercise. This is easier said than done! The bootcamp is 12 weeks long from 9am-5pm. You will spend evenings and weekends studying, improving your models, working on projects, blogging, updating your CV, job searching, networking, and more. However, you MUST carve time for yourself. Spend time with your loved ones, unplug, and have fun. Only you know what the right balance is, so make sure you follow through. Be kind to yourself, otherwise, you will not be able to take full advantage of your peers, your instructors, and the Metis staff. Get into a healthy routine if you do not already have one.
When it comes to technical abilities, once you are accepted into the bootcamp, you will receive pre-work assignments that cover various topics in Python, Linear Algebra, Statistics, and others. The sooner you get accepted into the program, the more time you will have to work on these skills and the better prepared you will be to tackle the fast-paced environment of the bootcamp.
What will my skills look like at the end of the bootcamp?
A consistent theme that I hear from all our alumni is that before they started the bootcamp, they could not have dreamed of completing the types of projects that they worked on during their time at Metis. See a few examples of our students projects here. These projects were completed in less than 4 weeks!
To complete these projects, our students became proficient in Python and several libraries such as NumPy, Pandas, Matplotlib, Scikit learn, and others. Similarly, they worked with both SQL and No-SQL databases. They learned about big data tools like Spark and Hadoop and used a wide range of supervised and unsupervised algorithms that include regression models, classification models, dimensionality reduction, clustering, and more. At the end of the program, they were also fluent in advanced topics such as Natural Language Processing and Deep Learning. Students also practiced their communication and visualization skills by presenting each of their projects in front of an audience. Their final project was presented at our Career Day event in front of an audience of companies looking to hire students!
Learn more about thet Metis Data Science Bootcamp and apply by the Final Application Deadline of Tuesday, May 29th!