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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
Arkansas
California
Colorado
Connecticut
Delaware
Hawaii
Illinois
Indiana
Louisiana
Maine
Maryland
Massachusetts
Minnesota
Mississippi
Missouri
Montana
Nevada
New Hampshire
New Jersey
New York
North Carolina
North Dakota
Ohio
Oregon
Pennsylvania
South Carolina
South Dakota
Tennessee
Vermont
Virginia
Washington
West Virginia
Request Curriculum
Become a competitive job applicant in the data engineering field with the Metis Data Science and Engineering Bootcamp. This program consists of expert-led classes and five projects, plus a full Career Week where we’ll help prepare you to find a job in the field.
APPLY
Expert Data
Science Instructors
Metis teachers aren’t just data scientists, they’re also experts at teaching and engaging students in an online classroom.
A Professional
Portfolio
Use the projects you complete during bootcamp to build a knock-out portfolio, and wow your interviewers.
Career Support Until
You’re Hired
Our career support is multifaceted. You’ll work with a dedicated advisor and get connected with our world-class hiring partners.
A Lifelong
Community
The Metis alumni community is something you want to be a part of. Connect, network, and make lifelong friends.
MODULE 1 -
MODULE 2 -
MODULE 3 -
MODULE 4 -
MODULE 5 -
UNIT 1: Exploratory Data Analysis Basics
Get a grasp on the basics of exploratory data analysis and how to use tools such as SQL and Python libraries.
Unit 2: Exploratory Data Analysis Advanced
Understand advanced SQL and Python methods used in Exploratory Data Analysis.
Project Due:
You’ll extract insights from a messy dataset. You will also use Jupyter notebooks to write code, the pandas Python package to perform exploratory data analysis, and packages like Matplotlib to visualize results. Finally, you’ll work with an SQL-based relational database to obtain, clean, and maintain data.
UNIT 1: Linear Regression Basics and Web Scraping
Learn the basics of linear regressions, feature engineering and cross validation, and how to webscrape.
Unit 2: Linear Regression Advanced
Learn about advanced methods in linear regression, including regularization and stochastic gradient descent. Plus, we’ll introduce you to time series regression methods.
Project Due:
You’ll solve a linear regression problem. You will gather data using web scraping tools and go in-depth into regression theory, practicing using python modules such as scikit-learn. Finally, you’ll apply foundational machine learning techniques such as validation and feature engineering.
UNIT 1: Advanced Coding and Cloud Computing
Learn advanced programming techniques, advanced database tools, cloud computing, and web application deployment.
Unit 2: Big Data
Learn the techniques and application of big data handling tools.
Project Due:
You’ll develop a modularized data processing pipeline, incorporating tools such as cloud computing, relational and non-relational databases, web application deployment, and big data handling tools (Hadoop or Spark).
UNIT 1: Classification Basics
Learn basic classification models, classification metrics, and feature engineering for classification problems.
Unit 2: Classification Advanced
Understand advanced classification models and how to work with imbalanced datasets.
Project Due:
You’ll solve a classification problem using algorithms such as KNN, logistic regression, Naive Bayes, decision trees, random forests, and gradient boosting. You’ll further explore the foundational concepts and techniques in supervised machine learning, determine the proper metrics to use for your modeling problem, and address potential challenges involving class imbalance.
UNIT 1: Natural Language Processing and Unsupervised Learning Basics
Learn the basics of natural language processing, recommendation systems, and dimensionality reduction. In addition, you’ll discover some basic clustering techniques.
Unit 2: Natural Language Processing and Unsupervised Learning Advanced
Learn advanced clustering algorithms and natural language processing techniques.
Project Due:
You’ll analyze text data using NLP algorithms. You’ll then utilize different techniques for dimensionality reduction such as Principal Component Analysis, apply clustering algorithms such as K-means, and learn topic models such as Latent Dirichlet Allocation.
Launch a new career with a full-time, immersive program that gives you plenty of engagement with instructors and peers.
Study on your own time with pre-recorded lectures. Structured modules, dedicated 1:1 instructor support, and assignment deadlines keep you on track.
Length
Tuition
Scholarship
Weekly Time Commitment
Schedule
Lectures
Instructors
Office Hours
Instructor 1:1s
Projects
Project Presentations
Career Support
Social Activities
Live Online
10 weeks
$14,500
$3,000
35-40 hours/week
Mon-Fri; 11am-6pm ET
Live Online
Metis Data Scientists
Weekly
Weekly
5
Live Online
Until Hired
Live Online
Online Flex
20 weeks
$7,700 $11,000
$3,000
15-20 hours/week
Flexible with deadlines to keep you on track
On-Demand
Metis Data Scientists
Weekly
Weekly
5
Live Online
Until Hired
Live Online
During Bootcamp
ONE-ON-ONE GUIDANCE
A dedicated advisor will help you map out your desired job location, industry, salary, and company.
SPEAKER SERIES
Join our speaker events where industry experts will share their experiences and give you advice.
JOB SEARCH TUTORIALS
On-demand videos will teach you to build your online presence, craft a resume, and network effectively.
The Week After Bootcamp
WORKSHOPS
Join our expert-led workshops and learn how to network, write a great resume, and practice for job interviews.
MOCK INTERVIEWS
Mastering the interview process takes practice. Work with our experts to nail your technical and non-technical skills.
Until You’re Hired
GRADUATE DIRECTORY
You’ll be added to our graduate directory automatically. It’s a place for hiring managers to view your profile, read your resume, and review your portfolio.
CONTINUED SUPPORT
We’ll support you until you get a job. Period. Plus, you’ll get access to our Alumni Portal where opportunities are posted regularly.
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.
How to Apply for the Data Science & Engineering 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 the Metis Data Science & Engineering Bootcamp include?
10 weeks of real-time classes (Live Online) or on-your-time modules over 20 weeks (Online Flex)
5 real-world data science projects
Career support throughout program & beyond
Individual support from your instructors & TAs
And much more!
Bootcamp modules are also offered as individual courses. This is a great choice if you’re interested in a specific topic or if you want to experience a taste of bootcamp, before committing.
