How to Become a Data Scientist in 12 Weeks with Metis
We caught up with Jason Moss (Co-founder of Metis) and John Harnisher (VP of Data, Analytics and Insight at Kaplan) to discuss the new Data Science course at Metis. Metis offers comprehensive courses in digital practices, designed to teach the skills needed to succeed in an increasingly digital world. The new Data Science course is a bootcamp that runs in-person for 12 weeks, Monday through Friday, from 9 am – 6 pm. We find out more details below.
Can you tell me a little bit about the motivations behind launching Metis and the Data Science course?
As we’ve been thinking about how we want to grow as a company and accelerate our digital footprint, we started looking into bootcamps. The reason for this was simple: they represent the perfect mix of great teachers and great curriculum with short intensive learning. We realised that this recipe works well and genuinely transforms people’s futures. At its core, this is Kaplan’s philosophy and bootcamps were really a way for people to move into high demand job areas.
With various reports like McKinsey’s suggesting that nearly 200,000 data science jobs will be unfilled because of the lack of skills, launching a course in this field was inevitable. The idea of a data science course really fit with what Metis was trying to do in terms of new economy skill training and bringing together great instructors with an intensive learning format to accelerate or change people’s careers.
How do you see the course matching the demand for Data Scientists?
The course we have created focuses on five practice-based projects, where each project goes through the same cycle of asking the most crucial questions and equipping the students with the skills to not only answer these questions but also execute the solution. The whole course is centred on this because we believe that it is important for candidates to show their prospective employers real-life projects in their portfolio, and to showcase a whole range of skills.
The second way we are filling this gap is by really focusing on communication. Of course, when we screen our applicants, we are looking for a certain level of programming, modelling and statistics skills. Crucially, however, we are also trying to assess whether the applicant communicates well. Why do we ask this, you may be wondering?
Well, at its core, Data Science is fundamentally about communication and we want to make sure that students have solid communication skills coming into the course. Once accepted, we ensure that there is a heavy emphasis on communication and visualisation because this is so pertinent to Data Science today.
There are a lot of other courses out there focusing on this. What is it about Metis that makes it different?
You can categorise these data sciences courses into three categories: MOOC’s, Masters programmes, and boot-camps. They all have their own value proposition.
With boot-camps, they are designed for people to have a very efficient path, develop a network, and opportunities to meet employers who are interested in hiring entry level data scientists. This is very different from a Masters programme, which requires a serious commitment of two years and considerable cash, and it is also different from MOOC’s, which cost but are usually free form.
Now, within bootcamps, there are a couple of data science courses but I think the way we have designed our course is unlike anything on the market. The ability to partner with a world-class practitioner in the data science space – Datascope Analytics – is also a huge advantage because they have real content expertise and have created a robust course that will give our graduates the skills they need for the roles they’re applying for.
Put Kaplan’s market leadership into the mix, and what you have is a programme that is backed by incredible experience, a forward thinking vision and a world-renowned syllabus.
How would you answer the sceptic who says “you cannot learn Data Science in 12 weeks”?
There are a couple of things here that we need to bear in mind. Firstly, we do not intend to recreate all of the knowledge someone would get over 5 or 10 years studying at a university. What we aim to do is teach a set of skills and get experience in these 12 weeks to make the person a great junior data scientist.
Also, it’s important to remember that this course is not designed for someone who has done a tiny bit of statistics, who knows a little bit about excel macros and programming. Rather, it’s a course people who have strong skills in a particular field – say analytics – but need to polish his or her programming skills, for example. We cannot take a total beginner and make them an entry-level data scientist, and we do not claim to do this.
What are they key things you look for in applicants?
Programming, stats and communication are the three core pieces we are looking for upfront. The application is designed to understand whether the applicant has these basics. After this, we look for a separate set of character traits that we believe is essential for a successful data scientist – curiosity, grit and creativity.
If someone is not inherently curious, they will struggle with the most fundamental and essential questions. Grit is all about the willingness to keep pushing because the questions data scientists deal with do not have easy answers. Creativity is simply the ability to think out of the box and use techniques that you may not be familiar with.
Our application is designed to make sure we get people who have the right skills and the right character traits.
A sidenote: we are currently accepting applications for our next bootcamp, which starts on January 12, 2015 in New York City. The early application deadline is November 17.
Do you have any plans to expand into Europe?
Absolutely. With a company that is as big as Kaplan, this idea is not designed to stay solely in New York. Of course, we need to prove that this models works before we start expanding overseas, but ultimately we believe that this course has a global audience and will only increase in popularity.
(Image Credit: Metis)