This full-time, 12-week data science experience hones, expands, and contextualizes the skills brought in by our competitive student cohorts. Incorporating traditional in-class instruction in theory and technique, students use real data to build a five-project portfolio to present to potential employers and have access to full career support throughout and after the bootcamp.Schedule a Chat with Admissions
12-Week, in-person Bootcamp
Monday - Friday, 9:30am - 6:00pm
2-3 hours of classroom instruction daily
4-6 hours of development and project work
Experience with programming
Experience with stats
Effective June 2, 2017, the tuition for the Metis Data Science Bootcamps in New York City, San Francisco, Seattle, and Chicago will increase to $16,000. Accepted students who have signed and returned their enrollment agreements on or before June 1, 2017 will receive the current tuition of $15,500. We recommend students apply by May 8, the Early Application Deadline for the Summer Bootcamp, to ensure enough time to go through the full admissions process. Not looking to enroll for the summer? Your enrollment can be deferred to a future cohort for the same tuition if received on or before June 1.
We partner with Skills Fund, an innovative financing company that offers financing options for students accepted to our bootcamp. Additionally, Metis part-time course alumni are able to apply the amount of tuition paid for one part-time professional development course toward enrollment in an upcoming Data Science Bootcamp upon admittance.
We also remain 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.
25 hours minimum of academic pre-work and variable hours to setup.
WEEK 1: Introduction to the Data Science Toolkit
Exploratory Data Analysis, Bash, Git & GitHub, Python, pandas, matplotlib, Seaborn
WEEK 2: Linear Regression and Machine Learning Intro
Web scraping via BeautifulSoup and Selenium, regression with statsmodels and scikit-learn, feature selection overfitting and train/test splits, probability theory.
WEEK 3: Linear Regression and Machine Learning Continued
Regularization, hypothesis testing , intro to Bayes Theorem
WEEK 4: Databases and Introduction to Machine Learning Concepts
Classification and regression algorithms (Knn, logistic regression, SVM, decision trees, and random forest), SQL concepts, cloud servers
WEEK 5: More supervised learning algorithms & web tools
WEEK 6: Statistical Fundamentals
MLE, GLM, Distributions, Databases ( RESTful APIs, NoSQL databases, MongoDB, pymongo) Natural Language Processing techniques
WEEK 7: Unsupervised Machine Learning
Various clustering algorithms, including K-means and DBSCAN, dimension reduction techniques (PCA, SDV, LDA, NMF)
WEEK 8: More Deep Learning & Unsupervised Learning
Deep Leaning via Keras, Recommender Systems
WEEK 9: Big Data
Hadoop, Hive & Spark, Final project initiated
WEEK 10-12: Final ProjectDownload Full Syllabus
Debbie, Chief Data Scientist at Metis, uses her "physics glasses" to solve challenging real-world problems and promote critical thinking.1/16
Michelle is passionate about the interplay between data science, creativity, and problem solving.2/16
Julia, a Metis data science instructor, loves using data to study and explore phenomena.3/16
Vinny, a Metis data science instructor, views data as a facet of perception.4/16
Brian is passionate about using data science to improve healthcare and enrich people's lives.5/16
Lingqiang loves extracting meaningful patterns from unstructured data and telling stories them.6/16
David has a penchant for solving novel problems with machine learning and revels in sharing knowledge with others.7/16
Jonathan Balaban is a consultant, data scientist, and entrepreneur with ten years of private, public, and philanthropic experience.8/16
Zach loves looking for kernels of truth hidden within data and using that knowledge to bring understanding into novel situations.9/16
Krishna comes to Metis from the advertising world having worked in a series of startups enabling online and television advertising.10/16
Taylan is an industrial engineer, mathematician and a data scientist with a passion for teaching and using data to solve real world problems.11/16
Paul, a Metis data science instructor, enjoys tackling open-ended problems a little outside of his comfort zone.12/16
Seth loves using math to turn organizations' data into money - and teaching others how to do the same.13/16
Andrew is passionate about helping people make rational decisions and building cool data products.14/16
Reshama uses her statistics, business and programming skills to explore data and share the knowledge with other data science enthusiasts.15/16
Roberto is a scientist with a strong background in data analysis and image/signal processing.15/16