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.
27 East 28th Street, 3rd Floor (WeWork Nomad) in New York’s Flatiron district.
633 Folsom Street, 6th Floor in San Francisco's SoMa district.
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.
We believe we are different in several key ways:
Curriculum: We take an iterative, project-centered approach to our data science bootcamp curriculum. On each of the five projects, we teach students how to identify the problem, extract and clean data, analyze and interpret data, and communicate the results, both visually and orally in a presentation. Metis focuses on the full lifecycle of being a data scientist, rather than just teaching theory or just teaching tools and technologies.
Career Support: The Metis Careers Team offers valuable tools and coaching before, during, and after the bootcamp to help students achieve their individual goals. There are one-on-one meetings with your Career Advisor, exposure to industry experts via our in-class Speaker Series, workshops focused on resume writing, LinkedIn, salary negotiations, mock technical interviews with professional data scientists, and more. Our team provides personalized, ongoing support to each student until s/he secures a job.
Accreditation: Metis is an accredited data science bootcamp. In order to keep our courses running, we must adhere to certain regulations determined by the Accrediting Council for Continuing Education and Training (ACCET). Our future is directly tied to our ability to help students get jobs related to data science.
Yes. The program requires full-time commitment Monday through Friday from 9am-6pm.
No, a job is not guaranteed. However, we do guarantee to:
While our hiring network is largest within our home cities of New York City and San Francisco—and therefore many local companies attend our Career Day events—we're also dedicated to helping those who wish to connect with companies based outside these areas. Our graduates currently work in 15 states and 7 countries.
Because Metis is backed by Kaplan, which has global reach, we have the ability to help introduce you to companies around the world. Our Career Advisors are 100% concerned with helping you find a job, not just in NYC and SF.
No, we do not provide living accommodations. We do partner with Common, which provides short-term collaborative living arrangements. If you want more information, please email us at firstname.lastname@example.org. There are also a number of other affordable short-term living options that you can research.
International Students may attend the Metis Data Science Bootcamp in New York City on an M-1 Visa. Details here.
Tuition: Tuition for the Metis Data Science Bootcamp is $15,500*. A deposit of $1,500 is required within 7 days of acceptance to secure a spot. After making the deposit, students have the option of paying in three monthly installments.
Scholarship: If you are a woman, a member of an underrepresented demographic group and/or community*, a veteran or member of the U.S. military, then you are automatically eligible to receive a $3,000 scholarship toward your Metis Data Science Bootcamp tuition.
* Underrepresented demographic groups include African Americans, Mexican-Americans, Native Americans (American Indians, Alaska Natives, and Native Hawaiians), Hispanic and Latino Americans, Pacific Islanders, and mainland Puerto Ricans.
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.
Admission into Metis is selective and is comprised of three phases. Prospective students must first submit a written application, which are reviewed by an Admissions Committee. To determine whether to advance a prospective student’s application into the next round of review, the Admissions Committee evaluates the applicant’s education and experience including (1) programming experience, (2) statistics experience, (3) effective communication skills, and (4) personality traits of curiosity, grit, and passion.
Prospective students who are advanced to the second round of screening are sent two challenges that include a technical assessment and a data science project challenge, which they have 48 hours to complete. Then, during a subsequent interview, conducted either in-person or online (e.g., Skype) by a Metis data scientist, the applicant presents their responses to the challenges (and the extra credit problems). While conducting each interview, the interviewer(s) evaluate, for a second time, an applicant’s demonstration of (1) programming experience,(2) statistics experience, (3) effective communication skills, (4) personality traits of curiosity, grit, and passion, as well as (5) motivation and (6) overall fit within Metis. If the Admissions Committee agrees that the person has the potential to succeed at Metis, the applicant is informed in writing of their acceptance into the program within two weeks of the interview.
Not sure if your skills and experience are strong enough for the Data Science Bootcamp? Try scoring yourself using this brief self-assessment:
Statistics total = _____
Programming total = _____
Personality total = _____
If you scored a six or greater in each of the above categories, you may be the kind of person we’re 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 seriously considered application.
Metis’ research shows a growing demand of employers seeking qualified individuals for positions in the field of Data Science. This is driven by the exponential growth of available data (2.5 quintillion bytes of data are created daily and 90% of the world’s data was created in the past two years) and the narrow set of specific skills required to extract value from that data. As a result, the number of job postings has surged and median salaries have risen as well, leading to “data scientist” becoming the best job in America in 2016, according to Glassdoor. The median salary for a junior data scientist is $95,000 - $104,000, depending on geography.
External data continues to validate the demand for the types of programs Metis offers:
We’ve certainly seen variation in regards to what employers have in mind when they use these terms, so please consider the answers below as general guidelines.
A Data Analyst is someone who creates and communicates insights from data to measure outcomes, make predictions, and guide business decisions. Often, there is a lighter coding burden placed upon someone with the title Data Analyst, though they may be expected to know certain languages or packages in R or python.
A Data Engineer is the designer, builder, and manager of the information or "big data" infrastructure. Each develops the architecture that helps analyze and process data in the way the organization needs it – and they make sure those systems are performing smoothly.
The term Data Scientist is used the most broadly. A job posting for a Data Scientist might describe a role identical to others calling for “data analyst,” though there is usually more diverse coding skills needed for a data scientist job. For the most part, data scientists are asked to participate in the entire cycle of problems and solutions. They help identify opportunities for companies to use data, while also finding, collecting, and integrating relevant data sources, performing analyses of varying degrees of complexity, writing code and creating tools that teams and businesses can use over time, and telling the story of what they’ve done to company stakeholders.
A computer science program tends to be more broad and theoretical. The Metis Data Science Bootcamp focuses on applications, so the computer science material covered within the bootcamp will be narrowly focused on topics in data structures, algorithms, input/output, and Python language that are pertinent to the data science workflow.
In addition, we cover topics in statistics and machine learning that are not computer science, per se. We also focus on the soft skills that make data scientists so valuable such as client interviews, communicating results, working with deadlines, perfectionism, and expectations.
Some experience in both programming and statistics are necessary. Further background in either one is helpful but not critical for this bootcamp. Students jump into solving problems directly, which requires the use of Python skills and statistics knowledge together. You will learn more in the area you’re currently weaker in (if that applies to you), meaning that you will graduate from the bootcamp feeling strong and qualified in both.
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.
Each student will spend approximately 25 hours of minimum academic work with additional hours to get set-up, download software, and review introductory materials depending on the student’s level of programming experience, statistics background, and available time.
As part of the pre-work, we provide a Command Line Crash course; tutorials to become familiar with Python; a number of package installation tutorials (i.e., Numpy, Scipy, pandas, Scikit.learn); and some preliminary linear algebra statistics work.
The pre-work is intended to provide students with the essential background and foundational knowledge they’ll need in order to start the Metis Data Science bootcamp.
You will need your computer, your brain, and a readiness to learn. Your computer needs to run OS X and have at least 4GB RAM, 2GHz, and a 100 GB HD. Alternatively, if you are a Windows user and your computer is fairly powerful, you could run a Linux Virtual Machine inside your normal Windows install. This requires some configuration.
You will complete five data science projects throughout the bootcamp. At the beginning, you follow along with the instructors as they guide you, but as you learn more, your control over each project increases. You soon make your own choices when tackling data science problems, and with each project, you get concrete, sharable results like blog posts, graphs, and/or reports. For each of these projects, you will conclude with a story of what the problem was, how you approached it, how you solved it, and what the results look like. The final project is your passion project, during which you have full control from start to finish. Aside from giving you hands-on experience and confidence, these projects provide you with stories and outcomes as a great way to demonstrate your abilities to potential employers.