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We are currently able to accept applicants for the live online bootcamp from the states listed below. We still encourage you to submit an app even if your state is not listed so we may notify you when we are able to move your application forward.
Arizona
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Connecticut
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Hawaii
Illinois
Indiana
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Maine
Maryland
Massachusetts
Minnesota
Mississippi
Missouri
Montana
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Oregon
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Request Curriculum
In our Live Online Data Science Bootcamp, you’ll build skills, make connections, and learn from data science experts. The bootcamp consists of 10 weeks of daily classes and five projects, plus a dedicated Career Week after graduation to help you find your next role in the data science field.
APPLY
Learn From Experienced
Data Scientists
Every class is led by industry-seasoned experts that must prove their instructional excellence.
Graduate with a
Project Portfolio
All bootcampers will complete five, portfolio-worthy projects that will impress employers.
Get Career Support
Until You’re Hired
We offer personalized career support and will help connect you with an extensive list of hiring partners.
Join a Lifelong
Community
Be welcomed into a community of active data professionals through our alumni network.
MODULE 1 - Exploratory Data Analysis
Week 1
Exploratory Data Analysis Basics
Learn to use and apply the core concepts of EDA by creating simple classes and exploring, manipulating, and describing tabular datasets using Python.
Week 2
Exploratory Data Analysis Advanced
We’ll expand on week one, diving deeper into Python and SQL methods used for Exploratory Data Analysis.
PROJECT
Show that you can extract insights from a messy dataset and work with an SQL-based relational database to obtain and maintain data. Plus, write code using Jupyter notebooks, perform EDA using Python packages, and visualize your results using packages like Matplotlib.
MODULE 2 - Linear Regression & Web Scraping
Week 3
Linear Regression Basics and Web Scraping
This week is all about web scraping, cross validation, feature engineering, and linear regression basics.
Week 4
Linear Regression Advanced
Learn the advanced linear regression methods which span topics from stochastic gradient descent to regularization. We’ll also teach you fundamental time series regression methods.
PROJECT
Your project for module two will cover two areas: solving a linear regression problem and applying foundational techniques for machine learning. How will you do this? You’ll go in-depth into regression theory, use python modules such as scikit-learn, and web scrape to gather data.
MODULE 3 - Business Fundamentals for Data Practitioners
Week 5
Business Analysis
We’ll use spreadsheet tools to analyze data and leverage data visualization best practices.
Week 6
Presentations, Project Management and Ethics
This week is about acquiring project management techniques, learning presentation skills, and exploring the ethical challenges of working with data.
PROJECT
This is your chance to apply your project management and iterative design knowledge to solve a business problem using data. You’ll take your findings and use them to build an interactive dashboard.
MODULE 4 - Machine Learning Classification
Week 7
Classification Basics
This week, we’ll cover topics like: featuring engineering for classification problems, basic classification models, and the fundamentals of classification metrics.
Week 8
Classification Advanced
Here, we’ll build on our foundational understanding of classification models by working with imbalanced datasets.
PROJECT
This is your time to show that you can solve a classification problem. How will you do that? By using algorithms such as decision trees, logistic regression, random forests, and Naive Bayes. Then, you’ll further explore techniques in supervised machine learning to determine the proper metrics for your modeling problem and address challenges with class imbalance.
MODULE 5 - NLP & Unsupervised Learning
Week 9
Natural Language Processing and Unsupervised Learning Basics
Learn the natural language processing basics, dimensionality reduction, and recommendation systems. Plus, you’ll be introduced to basic clustering techniques.
Week 10
Natural Language Processing and Unsupervised Learning Advanced
For your final week, you’ll learn advanced techniques in NLP and clustering algorithms.
PROJECT
This last project is an opportunity to analyze text data using natural language processing algorithms. In addition to this, you’ll utilize techniques for dimensionality reduction like Principal Component Analysis, apply topic models like Latent Dirichlet Allocation, and clustering algorithms such as K-means.
During Bootcamp
ONE-ON-ONE GUIDANCE
Career advisors will help you sort out your desired salary, industry, company, and job location.
SPEAKER SERIES
Industry experts will share their experiences and give tips and advice.
JOB SEARCH TUTORIALS
Learn how to draft a strong resume, build your online presence, and network effectively with these on-demand videos.
The Week After Bootcamp
WORKSHOPS
During live workshops, our expert Career Advisors will teach you how to finalize a strong resume, prep for interviews, put networking tips into action, and more.
MOCK INTERVIEWS
Practice and strengthen your interviewing skills with the help of our advisors.
Until You’re Hired
GRADUATE DIRECTORY
Your profile will be added to our directory so hiring managers can find you, view your resume, and explore your portfolio.
CONTINUED SUPPORT
Use our custom-built Alumni Portal to find job opportunities and get one-on-one support until you land a role.
10-Week, Full-time Bootcamp Program Schedule*:
Monday - Friday
11:00am - 6:00pm ET
10:00am - 5:00pm CT
8:00am - 3:00pm PT
*Includes independent project work and break.
PREREQUISITES
Experience with programming and stats
March 22 - May 28
Application deadline: February 22
April 19 - June 25
Application deadline: March 22
May 17 - July 23
Application deadline: April 19
June 14 - August 20
Application deadline: May 17
Check out our full program schedule for a list of comprehensive course dates.
During this recorded workshop, Roberto Reif, Executive Director of Data Science here at Metis, introduces you to an unsupervised machine learning algorithm used for clustering, called k-means.
Apply for the Metis Data Science Bootcamp
Don’t wait to apply. Applicants who are qualified will be accepted on a first come, first served basis.
The initial application takes between 10 - 15 minutes to finish.
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What does our live online Data Science Bootcamp consist of?
10 weeks of instruction
5 real-world data science projects
Individual support from your instructors & TAs
Career support throughout program & beyond
And much more!
Interested in a specific topic? Want to get a feel for bootcamp—before you enroll? All of our bootcamp modules are also available as two-week Short Immersive Courses.
