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DATA SCIENCE BOOTCAMP in New York City, Jan – Apr 2015

Learn Data Science in 12 weeks with in-person expert instruction - learn designing, implementing, and communicating the results of a Data Science project, including Data Visualization, modern Big Data tools and Hadoop stack.


Bootcamp dates: January 12 - April 3, 2015

Early application deadline: November 17, 2014
Final application deadline: December 8, 2014

Twitter: @thisismetis

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Learn Data Science in 12 weeks with in-person instruction at Metis with experts from Datascope Analytics. Upon graduating, students will be comfortable designing, implementing, and communicating the results of a Data Science project, including knowing the fundamentals of Data Visualization and having introductory exposure to modern Big Data tools and architecture such as the Hadoop stack.

Irmak Sirer, Data Science Instructor, Metis

20-30 hours of Online Pre-Work including a Command Line Crash Course, Python tutorials, several package installation tutorials (i.e., numpy, scipy, pandas, scikit.learn), and some preliminary statistics work.

WEEK 1: Project Benson
Complete first data science project from start to finish. Use the IPython environment and Git for version control, the pandas package to perform exploratory statistical analyses, and the matplotlib package to publish the results.

Weeks 2-3: Project Luther
Begin learning the iterative Design Process. Use tools for Web Scraping, get introduced to cloud computing, go in-depth on Regression using modules from scikit.learn and matplotlib and work on Communicating Results.

Weeks 4-6: Project McNulty
Focus on relational Databases such as SQL and more ways of obtaining, cleaning and maintaining data. Explore the concepts of Machine Learning.

Dive deep into Algorithms for Supervised Learning including SVM, decision trees and random forests; techniques for feature selection and feature extraction; concepts and applications for deep learning. Then, Visualize Projects using D3.js. Also cover JavaScript essentials, and other js libraries (e.g., jQuery, crossfilter, Bootstrap).

Weeks 7-9: Project Fletcher
Dig into text data, using Data Acquisition methods with APIs and online database servers. Learn about NoSQL databases and start using MongoDB. Analyze text data and learn about Naive Bayes and NLP algorithms and how large amounts of data are handled, discussing parallel computing and Hadoop MapReduce. Finally, explore Unsupervised Learning and more algorithms, covering K-means, hierarchical clustering, mixture models and topic models.

Weeks 10-12: Project Kojak
Project 5: Work full-time on your Passion Project, which is the capstone of your five- project portfolio to share with employers.


Students have access to a robust Speaker Series, which has included top experts from the New York Times, FiveThirtyEight, DataKind, Microsoft and Gilt. The Speaker Series serves two purposes for Metis students. Company experts visit the class to provide insight into a company's culture, job opportunities & specific interview processes. Industry leaders also attend to take students on a deep technical dive of new content to help expand the Metis students' skill sets.


A dedicated Career Team works full time to help students achieve their post-Metis goals. The Career Team works with the student throughout the program ensuring that the team can effectively advocate on the student's behalf. The students are trained in interviewing, resume-writing, and salary negotiation, are introduced to the Metis hiring partners and participate in an in-person Career Day at the culmination of the Bootcamp.


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