Chicago
Chicago
New York City
New York City
San Francisco
San Francisco
Live Online
Live Online
Chicago
Chicago
New York City
New York City
San Francisco
San Francisco
Live Online
Live Online
Premier Instructors
& Classmates
Learn and receive mentorship from industry-seasoned Data Scientists, while also collaborating with like-minded peers that have met our rigorous admission standards.
Project-Oriented
Curriculum
Our iterative, project-based approach enables students to apply what they’ve learned to 5 different data science projects, each concluding with a presentation of the results.
Career
Support
Career Advisors provide the curriculum, hiring partner connections, and individual support required to prepare you for a successful data science job search.
Active
Community
Our alumni and network of hiring partners create opportunities to constantly interact and engage with peers and practitioners in the data science community.
ONLINE
PRE-WORK
PROJECT 1:
Exploratory Data Analysis
PROJECT 2:
Regression & Web Scraping
PROJECT 3:
Classification & Interactive Dashboards
PROJECT 4:
Natural Language Processing & Unsupervised Learning
PROJECT 5:
Passion Project
PRE-WORK
WEEK 1
WEEK 2
WEEK 3
WEEK 4
WEEK 5
WEEK 6
WEEK 7
WEEK 8
WEEK 9
WEEK 10
WEEK 11
WEEK 12
ONLINE PRE-WORK
30 hours minimum of academic pre-work and variable hours to setup.
WEEK 1: INTRODUCTION TO THE DATA SCIENCE TOOLKIT
Python, Bash Shell, Git & Github workflow, data wrangling and EDA (Exploratory Data Analysis) with Python, pandas, and Matplotlib
WEEK 2: LINEAR REGRESSION, DESIGN PROCESS & WEB SCRAPING
Linear regression theory/application, web scraping via BeautifulSoup and Selenium, machine learning concepts (overfitting and train/test splits)
Week 3: Statistics Review, Intro Machine Learning & Communicating Results
Intro to time series modeling, statistics review, intro to Bayes Theorem, linear regression regularization, hypothesis testing
Week 4: Databases, Machine Learning Concepts, More Supervised Learning
Classification and regression algorithms (Knn, logistic regression, SVM, Naive Bayes), SQL concepts, cloud servers
WEEK 5: SUPERVISED LEARNING & VISUALIZATION
More algorithms (Classification and regression trees, Random Forest), interactive visualization with business intelligence tools, web dev essentials, Flask
WEEK 6: INTRODUCTION TO NLP, NoSQL & UNSUPERVISED LEARNING
NLP (textblob, NLTK, chunking, stemming, POS tagging, tf-idf) data & databases (RESTful APIs, NoSQL databases, MongoDB, pymongo), k-means
WEEK 7: MORE NLP, NoSQL, UNSUPERVISED LEARNING
More clustering algorithms (DBSCAN), machine learning topics (curse of dimensionality, dimension reduction, PCA, SVD, LSI), intro to deep learning & neural networks
WEEK 8: HANDLING BIG DATA
A/B testing experiment design and interpretation, distributed databases (Dask, Hadoop, HiveQL)
WEEK 9: BIG DATA MACHINE LEARNING, DEEP LEARNING, ETHICS & BEGIN PASSION PROJECT
PySpark, deep learning (CNNs, RNNs) data ethics, MapReduce algorithm, and final project initiated
WEEK 10-12: COMPLETE FINAL PROJECT & CAREER READINESS
While completing your final project, work with your career advisor to complete final one-on-one meetings and mock interviews. You'll also get the opportunity to network with companies actively seeking data scientists during career day.
12-Week, in-person Bootcamp
New Live Online Format Also Available!
Monday - Friday, 9:00am - 5:00pm
2-3 hours of classroom instruction daily
4-6 hours of development and project work
400 total clock hours
Experience with programming and stats
Third Party Financing
We partner with Skills Fund, an innovative financing company that offers financing options for students accepted to our bootcamp.
We are committed to creating a culture of inclusion within the exciting and growing field of data science. We aim to foster an equal and representative data science community amongst our staff and within our classrooms, filled with individuals of all technical, educational, and personal backgrounds.
Because of this, we offer $3,000 Data Science Bootcamp Scholarships to women, members of underrepresented demographic groups*, members of the LGBTQ community, and/or veterans or members of the U.S. military.
Why?
- Women make up less than one-third of all employees in the tech sector and just 11% of data scientists1 – additionally, they are paid significantly less, on average.2
- Women of color represent less than three percent of those in technology fields.3
- Only five percent of those in software development, application, and systems jobs are African-American and just five percent are Hispanic or Latino.4
- There are 20% fewer LGBT individuals in government STEM-related jobs than should be expected5 and 43% of the STEM workforce is closeted.6
We must reverse these trends and create more avenues for talented individuals from these groups and communities to enter, remain, and thrive in the field of data science.
* 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.
Scholarships & GI Benefits
We offer a $3,000 scholarship for women, members of underrepresented groups, the LGBTQ community, or veterans of U.S. military personnel. Learn about GI Benefits.
We are committed to creating a culture of inclusion within the exciting and growing field of data science. We aim to foster an equal and representative data science community amongst our staff and within our classrooms, filled with individuals of all technical, educational, and personal backgrounds.
Because of this, we offer $3,000 Data Science Bootcamp Scholarships to women, members of underrepresented demographic groups*, members of the LGBTQ community, and/or veterans or members of the U.S. military.
Why?
- Women make up less than one-third of all employees in the tech sector and just 11% of data scientists1 – additionally, they are paid significantly less, on average.2
- Women of color represent less than three percent of those in technology fields.3
- Only five percent of those in software development, application, and systems jobs are African-American and just five percent are Hispanic or Latino.4
- There are 20% fewer LGBT individuals in government STEM-related jobs than should be expected5 and 43% of the STEM workforce is closeted.6
We must reverse these trends and create more avenues for talented individuals from these groups and communities to enter, remain, and thrive in the field of data science.
* 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.
International Applicants
International students can attend the Metis Data Science Bootcamp in all of our U.S. campuses on an M-1 Visa. Details here.
We are committed to creating a culture of inclusion within the exciting and growing field of data science. We aim to foster an equal and representative data science community amongst our staff and within our classrooms, filled with individuals of all technical, educational, and personal backgrounds.
Because of this, we offer $3,000 Data Science Bootcamp Scholarships to women, members of underrepresented demographic groups*, members of the LGBTQ community, and/or veterans or members of the U.S. military.
Why?
- Women make up less than one-third of all employees in the tech sector and just 11% of data scientists1 – additionally, they are paid significantly less, on average.2
- Women of color represent less than three percent of those in technology fields.3
- Only five percent of those in software development, application, and systems jobs are African-American and just five percent are Hispanic or Latino.4
- There are 20% fewer LGBT individuals in government STEM-related jobs than should be expected5 and 43% of the STEM workforce is closeted.6
We must reverse these trends and create more avenues for talented individuals from these groups and communities to enter, remain, and thrive in the field of data science.
* 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.
Vinny, a Metis data science instructor, views data as a facet of perception.
Vinny comes to Metis after leading a team of Data Scientists at High 5 Games. Prior to that he taught Machine Learning at General Assembly and built tools for Animators and Effects Artists at Blue Sky Studios (the company that made Ice Age, Rio and The Peanuts Movie). He has a Masters in Computational Engineering and another in Creative Writing. He enjoys the nexus of mathematics, computer programming, human perception and arts. Over the past three years, Vinny has been knee-deep in large distributed data -- aggregating, building recommendation systems, measuring popularity and predicting Lifetime Value. In that time, he also finished a first draft of his novel. An avid programmer, Vinny has won various programming contests including the Regional ACM Collegiate Programming Contest. He has taught at the University of Miami and has given talks and presentations at various colleges and conferences.
Check out content by and/or featuring Vinny:
Alice, a Metis data science instructor, enjoys making complex things easy to understand.
Alice comes to Metis from Cars.com, where she started as the company's first data scientist, supporting multiple functions from Marketing to Technology. During that time, she also co-founded a data science education startup, Best Fit Analytics Workshop, teaching weekend courses to professionals at 1871 in Chicago. Prior to becoming a data scientist, she worked at Redfin as an analyst and at Accenture as a consultant. She has her M.S. in Analytics and B.S. in Electrical Engineering, both from Northwestern University. She blogs about analytics and pop culture on A Dash of Data. Her blog post, "How Text Messages Change From Dating to Marriage" made it onto the front page of Reddit, gaining over half a million views in the first week. She is passionate about teaching and mentoring, and loves using data to tell fun and compelling stories.
Check out content by and/or featuring Alice:
Podcast: Data Science for Beginners (Learn to Code with Me Podcast)
Talk: Support Vector Machines: A Visual Explanation with Sample Python Code
Article: Geek of the Week (GeekWire)
Joe loves tackling unusual problems with the tools of data science and has a passion for effectively communicating quantitative ideas.
As both a math enthusiast and a former competitive debater, Joe was drawn to data science by its place at the intersection of statistics, computing, and communication. He has worked on projects ranging from quantifying and comparing story plots to building a Bayesian model of human rights abuse rates that accounts for informational bias. Before transitioning into data science, he worked in various data analytics roles, most recently as an Equity Research associate on Credit Suisse's portfolio strategy team. He holds a B.A. in Mathematics from Columbia University, and is also a Metis alumnus. He currently coaches NYU's parliamentary debate team, and in his free time he enjoys playing piano, reading, and playing board games.
Check out content by Joe:
Article: Safety in Numbers: My 18th Place Solution to Porto Seguro’s Kaggle Competition
Kimberly uses her background in applied math to discover data's what, why, and how.
Kimberly joins Metis from MRM//McCann, a leading digital advertising agency, where she focused on helping clients understand their customers by leveraging unstructured data with modern NLP techniques. She is passionate about data storytelling and the power of compelling data visualizations to challenge pre-conceived assumptions. Kimberly's enthusiasm for teaching comes from her days as an academic. She holds a Ph.D. in applied mathematics from Rensselaer Polytechnic Institute and completed a postdoctoral fellowship in math biology at the Ohio State University. In her spare time, Kimberly likes to stay active and particularly enjoys swing dancing, rollerblading, and jogging with her dog.
Check out content by Kim:
As a former teacher assistant for several courses at Columbia, Richard is excited to share his knowledge of data science, academic and industrial, with aspiring data scientists of all backgrounds.
Richard Chiou holds a BA in Computer Science and Economics-Mathematics from Columbia University and a Master of Engineering degree in Data Science and Systems from UC Berkeley. He joins Metis from Signifyd, where he worked on machine learning models for online e-commerce fraud prevention. In his spare time, he is a board game enthusiast, a frequent escape room artist, and an intrepid traveler who seeks to uncover the mysteries and pleasant surprises hidden in life.
Chris Bruehl, a Data Science Instructor, enjoys empowering others to turn data and algorithms into clear business results.
Chris has always had a passion for business and mathematics, which led him to his undergraduate degree in Economics at Cal Poly. After working in international supply chain management for several years, he realized the best part of his day was sitting down with a cup of coffee and crunching data, so he returned to school to get his Masters Degree in Analytics at North Carolina State University. He brings 4 years of data science experience in the insurance industry, working on a wide array of projects from customer conversion modeling to fraud detection. In his spare time, he is a dog dad, gamer, and vinyl record hunter.
Joan is a data scientist who specializes in the intersection of data, policy, and society.
Joan comes to Metis from Omelas, where she built machine learning models and data pipelines that map the online information environment around geopolitical actors. She used data analytics to explore challenging policy questions about digital technologies at the Urban Institute and EducationSuperHighway. Prior to her transition into data science, Joan worked with PwC Forensics Advisory to serve technology firms in the Bay Area. Joan received her M.S. in Computational Analysis and Public Policy from the University of Chicago and completed her undergraduate studies at the University of California, Berkeley, with B.A.’s in Economics and Operations Research & Management Science.
Hiring Network
Gain access to our robust hiring network, cultivated by our Career Advisors throughout the years. You’ll be connected to hiring managers at top companies across industries.
Career Curriculum
Participate in weekly workshops on resumes, networking, interview preparation, salary negotiations, plus mock technical interviews and more to ensure you’re ready upon graduation.
Post-Graduation Support
Receive access to our custom-built Alumni Portal where our hiring partners’ open roles are posted. You’ll also connect with past graduates on our exclusive Alumni Slack to widen your network.
Workshops
Engage in workshops like resume writing, salary negotiations, and more.
One-On-Ones
We discuss salary, location, industry, and culture to best align you with the right company and career.
Mock Interviews
Participate in a practice technical interview with professional data scientists.
Company Site Visits
Visit hiring partners’ offices and network with their data science teams.
Speaker Series
Learn from industry experts through our Speaker Series. View past speakers here.
Career Day
Present your final passion project to employers and meet hiring companies.
“We’ve been working with Metis for a few years now across several different geographies. Their talent bar is extremely high, and we repeatedly hire very strong candidates from them. Their curriculum, staff, and career partners tend to produce candidates that pass our rigorous interview process and then hit the ground running once they start.”
1
SUBMIT YOUR
APPLICATION
2
COMPLETE TECHNICAL
ASSESSMENT
3
INTERVIEW WITH
A DATA SCIENTIST
4
WELCOME
TO METIS!
Our applicants come from diverse backgrounds. We recommend you at least have some experience with programming and statistics. Upon submitting your application, you will be matched some alumni with similar backgrounds so that you may reach out if you’d like to get their experience in the bootcamp.
1
SUBMIT YOUR
APPLICATION
Our applicants come from diverse backgrounds. We recommend you at least have some experience with programming and statistics. Upon submitting your application, you will be matched some alumni with similar backgrounds so that you may reach out if you’d like to get their experience in the bootcamp.
2
COMPLETE TECHNICAL
ASSESSMENT
After initial review of your application, our team will invite you to complete a technical assessment. It features a mix of questions in math, statistics, python, and basic intuition in working with data.
3
INTERVIEW WITH
A DATA SCIENTIST
Once you’ve successfully completed your challenges, you’ll get an opportunity to interview with a Data Scientist to further dive into your technical background, discuss your goals, and brainstorm on your project idea.
4
WELCOME
TO METIS!
Congratulations on making it into one of our Bootcamps! We pride ourselves on having a highly selective and rigorous admissions process. This in part ensures you and your peers are setup for success. Now the real fun begins; Complete the pre-work materials in order to feel prepared and ready to tackle day 1!
Join us on Tuesday, June 30 from 1-2pm ET for our next One Hour at Bootcamp!
Book A Tour
Come explore one of our campuses and meet our team! We’d love to show you around.
We are committed to creating a culture of inclusion within the exciting and growing field of data science. We aim to foster an equal and representative data science community amongst our staff and within our classrooms, filled with individuals of all technical, educational, and personal backgrounds.
Because of this, we offer $3,000 Data Science Bootcamp Scholarships to women, members of underrepresented demographic groups*, members of the LGBTQ community, and/or veterans or members of the U.S. military.
Why?
- Women make up less than one-third of all employees in the tech sector and just 11% of data scientists1 – additionally, they are paid significantly less, on average.2
- Women of color represent less than three percent of those in technology fields.3
- Only five percent of those in software development, application, and systems jobs are African-American and just five percent are Hispanic or Latino.4
- There are 20% fewer LGBT individuals in government STEM-related jobs than should be expected5 and 43% of the STEM workforce is closeted.6
We must reverse these trends and create more avenues for talented individuals from these groups and communities to enter, remain, and thrive in the field of data science.
* 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.
Take The First Step
Ready to take the first step toward becoming a Data Scientist? Start your application.
We are committed to creating a culture of inclusion within the exciting and growing field of data science. We aim to foster an equal and representative data science community amongst our staff and within our classrooms, filled with individuals of all technical, educational, and personal backgrounds.
Because of this, we offer $3,000 Data Science Bootcamp Scholarships to women, members of underrepresented demographic groups*, members of the LGBTQ community, and/or veterans or members of the U.S. military.
Why?
- Women make up less than one-third of all employees in the tech sector and just 11% of data scientists1 – additionally, they are paid significantly less, on average.2
- Women of color represent less than three percent of those in technology fields.3
- Only five percent of those in software development, application, and systems jobs are African-American and just five percent are Hispanic or Latino.4
- There are 20% fewer LGBT individuals in government STEM-related jobs than should be expected5 and 43% of the STEM workforce is closeted.6
We must reverse these trends and create more avenues for talented individuals from these groups and communities to enter, remain, and thrive in the field of data science.
* 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.
Chat With Admissions
Have more questions about our data science program? Our admissions team is happy to speak with you.
We are committed to creating a culture of inclusion within the exciting and growing field of data science. We aim to foster an equal and representative data science community amongst our staff and within our classrooms, filled with individuals of all technical, educational, and personal backgrounds.
Because of this, we offer $3,000 Data Science Bootcamp Scholarships to women, members of underrepresented demographic groups*, members of the LGBTQ community, and/or veterans or members of the U.S. military.
Why?
- Women make up less than one-third of all employees in the tech sector and just 11% of data scientists1 – additionally, they are paid significantly less, on average.2
- Women of color represent less than three percent of those in technology fields.3
- Only five percent of those in software development, application, and systems jobs are African-American and just five percent are Hispanic or Latino.4
- There are 20% fewer LGBT individuals in government STEM-related jobs than should be expected5 and 43% of the STEM workforce is closeted.6
We must reverse these trends and create more avenues for talented individuals from these groups and communities to enter, remain, and thrive in the field of data science.
* 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.
