Executive Director of Data Science and Strategy at Metis, Roberto Reif, shows us how the data science bootcamp transitioned to remote learning in 2020, what to expect from the admissions process, and how they support students in getting hired post-bootcamp. With the recent launch of four specialized bootcamps and seven new courses in topics like Exploratory Data Analysis and Deep Learning Fundamentals, anyone interested in data science and analytics can find a path into the field at Metis. Plus, Roberto shares a virtual tour of their online data science bootcamp classroom and explains why now is the perfect time to begin a career in data.
Why has Metis decided to completely transition to remote learning in 2020?
Metis made the decision in 2019 to move online, launching our first online bootcamp in January 2020. By the time COVID-19 hit, it was relatively easy for us to transition all our physical campuses online. We learned that student satisfaction in the online version was as high as ever, which confirmed and accelerated our decision.
Transitioning online appealed to us for two reasons: the ability to reach a broader population of students around the world, and the ability for students to access each other.
Remote learning prepares students to work remote jobs, which we have already seen is a trend moving forward. It is important to be able to work in a remote setting and interact well and efficiently with people all over the world.
How has the transition online changed how Metis approaches traditionally in-person or community-based events?
We focus a lot on presentation and storytelling skills. We have always had guest speakers, people from industry come to Metis and talk to our students about what it's like to work at their company, the hiring process, etc. Now, those events take place online.
We also have a Graduate Directory on our website where students can self-promote with a brief bio and a project they’ve completed. We share this directory with over 500 hiring partners with whom we work.
During COVID-19, Metis has actually launched several new bootcamps – tell us about the new topics you’re teaching!
In talking with incoming students, alums, and hiring partners to understand new trends, we’ve discovered that there is no universal fit for every student and that students enter the program with different needs and requirements. For example, some students want to work in the latest, cutting-edge technology in deep learning, while other students are more interested in solving classical data analytics business problems.
In response to this, we created seven two-week Short Immersive Courses, each touching on a specific topic within the field. These topics are: Exploratory Data Analysis, Regression Models & Web Scraping, Classification, Deep Learning, and others.
Students can take these short immersive courses as standalones, or courses can be stitched together for a Bootcamp Certificate. Depending on the combination of the courses taken, we provide a specific certificate in fields like:
What is the difference between a Short Immersive Course and a Bootcamp Certificate?
Bootcamp Certificates are tied to a Career Services Team, who work with students from the moment bootcamp starts to the moment they are hired. The week after the bootcamp, we offer a dedicated Career Week to go through mock-interviews and workshops on: finalizing a strong resume, building a LinkedIn profile, how to network, and how to negotiate salaries.
Additionally, we notice that students have different sensitivities to the duration and cost of the program. We now offer four bootcamps:
We also just launched seven live, online Short Immersive Courses for students who want to gain in-demand data science and analytics skills in just two weeks. Unlike the bootcamps, there is open enrollment, with no admissions process. Students apply what they’ve been taught to a final project at the end of the two weeks that can be added to a professional portfolio. These courses will also provide an opportunity to see what the bootcamp experience is like (all cost $3,500):
Students have access to Google Calendar - with an hourly breakdown of what to expect throughout the day.
They start with a Pair Problem: In a group of two, students are given a challenge that they have 45 min to solve, serving one of three purposes. Challenges may be:
Expectations are clear. There is a description of what the function is supposed to do and examples of test cases indicating what the results should look like. At the end, the students are brought back together to share and discuss their solutions, and the instructors might offer some more efficient solutions that the students might not have thought about.
What has been the biggest difference between in-person and online at Metis?
Trying to learn how to deliver lessons online vs in-person is a different ball game. Even if you're teaching the same topics, the way to communicate with students is different. One benefit at Metis is our parent company, Kaplan. Within Kaplan, we have the Learning Sciences Team; their focus is on understanding how students learn in any setting, in-person or online.
Analyzing how people learn online is a new field; by working closely with their cutting edge research, we're able to get best practices on how to apply tools that exist today in an online setting.
What tools does Metis use to teach data science?
Zoom, Slack, Google Calendar, Github, Calendly for 1:1 scheduling.
Who is the ideal Metis bootcamper?
We are mainly looking for potential in prospective students. It's not so much the knowledge that they have, but rather, their ability to succeed and grow within the program. The minimum requirements to get into Metis is the ability to program in Python and basic math skills such as Calculus and Algebra.
What have your most successful students done throughout online learning? Is there a trick?
One of the challenges in the data science field is: when you get hired by a company, you're not necessarily getting hired by what you know, you're getting hired by your ability to solve problems - whether you know how to solve them right now or not.
Successful students: create community, problem-solve, self-rely, persevere, and have grit.
How can beginners or those without a STEM background prepare for Metis?
Historically, Metis has seen students from a wide range of backgrounds. It's not unique to what's happening now with the pandemic. We have students that come from the typical STEM backgrounds, as well, we have students who have been: baristas, minor league baseball players, musicians, artists, and so on. Students enter the program with a wide range of skills and they graduate with more, new skills.
To get into the bootcamp, we expect students to have a minimum technical ability in Python and math. Some students already have that technical ability, so they apply, complete a technical assessment and an interview, and they get into the program. Others don't have that background or need a refresher. We offer bootcamp prep courses that happen every few weeks, where people can sign up to get the skills of what they need in Python and math. If they enroll in the bootcamp, we roll the cost of that course into the bootcamp, so they end up not paying for it.
What is your personal teaching style, Roberto?
First, I use a method called Chunking. This is built into the curriculum – we take a two-hour lesson and break it down into 5-15 min chunks that cover a specific learning objective. After that chunk, we take a pause and test for it, using polling functionalities, asking questions, or placing students in breakout rooms to discuss what was covered in that small chunk.
Secondly, studies show two extreme sets of students: one studies for a test by cramming the night before without doing anything beyond that; the other is a student that, throughout the semester/quarter has been alternating studying and sleeping. Interestingly, both can do fairly well on the test the next day, but a few days after the test, the person who crammed at the last minute is going to forget most of it, while the person who has been consistently studying is gonna be able to retain things more.
We've modified our curriculum to enable that ability. We teach a concept on Monday and we touch on that topic again on Wednesday with a review that ties it together with everything else, doing the same thing on Friday. We are constantly using this repeatability; allowing students to sleep over these concepts and supporting them in moving this new knowledge from short-term to long-term memory.
Metis has been around for seven years. There are two aspects to how we teach our bootcamp:
What is data science job placement like in 2020 at Metis?
In March, we saw companies go through a hiring freeze. Graduates in the middle of the interview process then got put on hold for a period of time. As the world figured out the new normal of working remotely during a pandemic, companies started reopening their hiring practices. In the Summer, we noticed an uptick of our students getting hired.
One of the great challenges we had in the last cohort is that when students graduate, we hire some of them to be teaching assistants in the next cohort while they're doing their job search. Our students have been getting hired so quickly that we're constantly hiring new TAs and onboarding them. It's a great problem to have.
Our Careers team has been attuned to the new normal and have revamped all our workshops to include topics like How To Do a Job Search (during a pandemic).
What's the best advice you’ve heard about how to get a data science job after a bootcamp?
The best advice I can offer regarding students getting jobs after bootcamp is to work with the Careers team. They've seen it all and can & will assist you in getting hired. We have over 1200 alums that have graduated from our program and the Careers Team has supported every one of them in getting jobs. Share where you are and take their advice.
Pay-it-forward. Students come through the bootcamp, work hard, and learn new things.
For some challenges, they were able to Google and find an answer quickly; others required a deeper search to figure out how to put things together. When a student goes through that process, I recommend sharing that knowledge with others through blogs or GitHub. As you slowly become an expert and become a part of the community, pay-it-forward for the next person who's trying to solve a similar problem as you have. Employers see this extremely favorable, as a person that is part of the community and helping others. The ability to build community outside of themselves extends to the career search.
Why is right now the best time for someone to make a career change into data science?
The demand is high and it's going to continue to grow. One of the great things is data is everywhere; every company, from brick & mortar to top corporations all work with data. The jobs are more frequently remote, meaning you can be located everywhere. Ask yourself – Are you interested in the field? Do you want to work with data? Jumping into a field that is exciting but not interesting is not going to serve well. However, if you do have the interest, if you do like working with data, this is one of the hottest jobs out there. LinkedIn just released their 2020 Emerging Jobs Report and Artificial Intelligence Specialists saw a 74% annual growth, Data Scientists a 37% annual growth, and Data Engineers a 33% annual growth.
The mission of Metis is to enable people to find value in data. That's where our passion lies. Incoming students worry if they have the skills to succeed at Metis. When we talk with hired graduates, their feedback is that they wish they'd started sooner. To me, that's the key message; if you're considering a transition, try to start sooner than later. You're never gonna be perfectly prepared, but having the grit to follow through is what will make you very successful.
Brook from Code Fellows compares Python vs Java – and tells you which you should learn first!
LearningFuze's new Part-Time Data Science Bootcamp was created for working adults!
Here's how NGT Academy supports the next generation of cybersecurity professionals...