FAQ

General


General

What is Metis?

Metis accelerates the careers of data scientists by providing full-time immersive bootcamps, evening professional development courses, online training and corporate programs. Courses are taught by expert data science practitioners, integrating project based learning with real data sets.

What makes Metis superior to other programs?

We believe we are different in several key ways:

World Class Practitioners:

Datascope Analytics Datascope Analytics is an elite data-driven consulting and design firm in Chicago. As big data has continued to become a valuable asset within organizations, they have been able to solve big data problems for some of the largest employers by serving in the space where analytics intersects consulting and design. Data science and visualization is a rapidly evolving field and Datascope Analytics with a team of data scientists, entrepreneurs and designers have embraced the ambiguity and promoted an environment of learning and diversity of thought. They have harnessed their culture of problem solving, openness and learning and applied it to the creation and teaching of the Metis course.

Curriculum: The Metis data science curriculum combines the expertise of world class practitioners with Kaplan’s expertise in learning science, assessment and motivation. Not only will you be working on your portfolio from day one (with weekly deliverables), but you will also get the chance to work on a project like you would in a real world experience.

Employer Network: Metis not only has relations with more than 100 companies hiring data scientists, but can also introduce you to a very large hiring partner network comprised of companies within Datascope Analytics’ client network and Kaplan’s global reach and employer network.

Alumni Network: Datascope Analytics and Kaplan launched Metis with the goal of creating a global business. Kaplan is a $2 billion company that is prepared to invest in the success and scaling of Metis. This means that, over time, your alumni network will be considerably large and robust. You’ll have private access to a growing list of graduates to give advice to each other, ask career questions, celebrate success, and help make introductions to potential employers.

Is Metis accredited?

Yes. Kaplan, Inc. launched Metis in 2014 and has been awarded accreditation by the Accrediting Council for Continuing Education & Training (ACCET) for all Metis data science programming. ACCET has been recognized by the U.S. Department of Education since 1978, and Kaplan Test Prep, a division of Kaplan, Inc. has received back-to-back 5-year grants of recognition — the longest period provided to an accredited member school. The rigorous standards prescribed by ACCET include demanding review and approval of the Metis curriculum, of instructional personnel, of instructional delivery, and of admissions and student services.

Is this a full-time commitment?

Yes. The program requires full-time commitment Monday through Friday, from 9AM-6PM.

Does this program guarantee a job at the end?

No, a job is not guaranteed. What we guarantee is that:

  • We will work insanely hard to provide you with a great Data Science learning experience.
  • We will introduce you to many hiring partners who are looking to hire entry-level data science professionals.
  • We will provide post-session support and professional development through our teachers and our Career Managers.

What if I want to pursue a job that is not in the city where Metis runs classes?

Our hiring network may be largest in our home cities (NYC,SF) and therefore we have a lot of local companies attend our Career Day in our home city, but…

  • We're also going to help connect you with companies not based in New York City or San Francisco.
  • Because Metis is backed by Kaplan, which has global reach, we have the ability to help introduce you to companies around the world.
  • Finally, our Career Advisors are 100% concerned with helping you find a job...not just find a job in New York City or San Francisco

Does Metis provide living accommodations?

Metis does not provide living accommodations. There are a lot of affordable short-term living options that you can research. We also partner with Common, which provides short-term collaborative living arrangements. If you want more information, please email us at housing@thisismetis.com.

Does Metis provide visas?

We do not currently provide visas.

What are the payment options for Metis?

Tuition: The tuition for Metis Data Science Bootcamp is $14,000*. A deposit of $1,500 is required within 7 days of acceptance to secure your spot. After making the deposit, students have the option of paying in three monthly installments.

*Notice: Tuition Increasing June 20. Details

Third Party Financing: Students accepted into Metis also have the option to explore financing through Skillsfund.

  • Longer term loans with low interest rates and the option to pay interest-only while in school.
  • 36 month- 5.99%* interest rate for interest only and deferred payment loans
    60 month- 7.99%* interest rate for interest only and deferred payment loans
  • 36 or 60 month terms
  • Deferred Payment available
  • 3.0% origination fee
  • Borrow up to the full tuition amount less $1500 deposit

* Does not include 3% origination fee

Scholarship:

All women and underrepresented minorities (includes African Americans, Mexican-Americans, Native Americans (American Indians, Alaska Natives, and Native Hawaiians), Hispanic and Latino Americans, Pacific Islanders, and mainland Puerto Ricans, and veterans or members of the U.S. military are eligible for a $2,000 scholarship to apply toward their tuition.

Can I use 529 funds to pay the Metis tuition?

No. Although Metis is accredited by ACCET, we are not accredited as a Title IV organization, therefore we do not qualify for the use of these funds.

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Data Science

Where does Metis run its classes?

NEW YORK CITY

27 East 28th Street, 3rd Floor (WeWork Nomad) in New York’s Flatiron district.

SAN FRANCISCO

633 Folsom Street, 6th Floor in San Francisco's SoMa district.

Application Process?

Our application process is divided into three phases. The written application, a coding challenge and then a video-chat or in-person interview. Only those applicants that make it through the written application stage will participate in the coding challenge and interview. We will accept people into the program on a rolling basis. We recommend spending time on the written application. It is a competitive application process.

Am I qualified for the Data Science bootcamp?

If you aren’t sure if your skills and experience are strong enough for the Data Science bootcamp, try scoring yourself on this brief self-assessment.

Statistics

  • [+5] Have you ever performed quantitative or qualitative research?
  • [+5] Have you ever built a computational model of something?
  • [+2] Do you know what the Monty Hall problem is?
  • [+3] Can you explain why it works?
  • [+2] Have you ever been bothered by a news story, report, figure, or infographic that had a flaw in its quantitative analysis?
  • [+2] Have you ever caught (or gone back to search for) an error in your work because the result you had seemed fishy?
  • [+2] Have you ever taken a stats class... and liked it?

Statistics total = _____

Programming

  • [+2] Have you ever written code to achieve a goal?
  • [+4] Have you written code to do something that no one assigned or paid you to do?
  • [+4] Have you ever written code to do something for you that you were asked to do by hand?
  • [+2] Have you ever experienced a "debugger's high" (bliss, excitement, or elation resulting from figuring out why your code isn't working)?
  • [+4] Could you name more than three data structures off the top of your head?

Programming total = _____

Personality

  • [+2] Have you ever been accused of being "obsessive" for the amount of effort you've put into finding a satisfactory answer to an unimportant or trivial question?
  • [+2] Have you ever said, "You know, I bet we could test that..." and then started designing a study or experiment? (in your head counts)
  • [+2] Have you ever found yourself incidentally "interviewing" someone about what they do and how they do it?
  • [+2] Have you ever done this in an odd environment, like at a party or a bar?
  • [+2] Have you ever taught someone about something just because it makes you feel good?

Personality total = _____

If you scored a six or greater in each of the above categories, you may be the kind of candidate we are looking for. Of course, the bootcamp itself will be much more challenging, involved, and technical. But this assessment highlights the combination of skills, interests, and personality we think are necessary for a serious application.

Is Data Science an in demand occupation?

It is a very promising landscape for Data Science jobs. A Mckinsey Study conducted in 2011 predicted “there will be a shortage of talent, particularly of people with deep expertise in statistics and machine learning...By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills.” This continues to be a growing field and one that requires a unique skillset and background.

What is the difference between a data scientist, data analyst, and data miner?

We have seen a lot of variation in what employers might have in mind when they use these terms, so use the answers below as general guidelines.

A data analyst is usually someone who works within a company and helps to make and communicate insights from their data to measure outcomes, make predictions, and guide business decisions. Often there is a lighter coding burden for someone with the title “data analyst,” though they may be expected to know certain languages or packages in R or python.

A data miner’s role might be very similar to a data analyst’s, though use of the term “mining” usually carries the connotation of working with large datasets to find patterns and extract insights.

The term “data scientist” is used the most broadly. A job posting for a data scientist might describe a role identical to others called “data miner” or “data analyst,” though there is usually more and more diverse coding skills needed for a data scientist job. For the most part, though, data scientists are asked to participate in the whole cycle of problems and solutions - they help identify opportunities for companies to use data, find, collect and integrate relevant data sources, they perform analyses of varying degrees of complexity, they write code and create tools that teams and businesses will use continually over time, and they tell the story of what they have done to stakeholders.

How is this different than a Computer Science program?

A CS course tends to be much more broad and theoretical. The Data Science bootcamp will be focused on applications and the CS we cover will be more narrowly focused to topics in data structures, algorithms, i/o, python language as are pertinent to the data science workflow.

In addition, we cover topics in statistics and machine learning that are not really computer science per se. Finally, we provide a lot of experience in the soft skills that make data scientists so valuable - client interviews, communicating results, working with deadlines, perfectionism, and expectations.

Is it more important to have a background in Python or Statistics?

Some experience in both programming and statistics are necessary. Further background in either one is helpful but not critical for this bootcamp. You will jump into solving problems directly, which requires use of Python skills and statistics knowledge together. This means you will learn more in the area you have less of a background in. No matter which part you started strong at, you will have the complete skill set and confidence at the end.

What tools will be used in the course?

Students will build a strong foundation in python-language, the unix/linux command line, machine learning packages such as scikit.learn, other statistics modules including scipy and pandas, web scraping packages like BeautifulSoup and Selenium WebDriver, PostgreSQL and mongodb databases, collaborative coding under version control with git, working on remote cloud servers such as rackspace, custom visualization tools, especially matplotlib and d3.js with support in HTML, CSS, javascript and web hosting.

They will also learn about (and become familiar with) distributed algorithm frameworks such as Hadoop/MapReduce, system architectures with multiple servers of different roles, and web app frameworks such as Django.

What can I do to get ready before the course starts?

Each student will spend 20 to 30 hours doing online Pre-work before the start of the class. We provide a Command Line Crash Course, tutorials to become familiar with Python, and a number of package installation tutorials (i.e., numpy, scipy, pandas, scikit.learn), as well as some preliminary statistics work. Test-out/check-out modules will let students know when they are "prepared enough" for class.

What do I need to bring to class?

You will need your computer, your brain and a great personality. Your computer needs to run OS X and have at least 4GB RAM, 2GHz and a 100 GB HD.

I want to have something concrete to show potential employers. What will I build during the course?

You will complete multiple data science projects throughout the bootcamp. At first, you will be following the instructors, but as you learn more, your control will increase and you will make your own choices when tackling these data science problems. These projects will produce results like blog posts, graphs, or reports. For each of these projects, you will have a story of what the problem was, how you approached it, how you solved it, and what the results look like. The final project will be your passion project, where you will have full control, from start to finish. Besides giving you hands-on experience and confidence, these projects will provide you the stories and outcomes as a great way to demonstrate your abilities to potential employers.

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