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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
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West Virginia
Request Curriculum
The online Data Science and Machine Learning Bootcamp features expert-led classes, projects, and individual guidance. After graduation, you’ll attend Career Week, where advisors will help you perfect your resume and interviewing skills.
APPLY
Learn with Top
Data Science Instructors
Industry-seasoned expert teachers will lead you to success through their engaging live online classes.
Graduate with a
Portfolio of Projects
You’ll leave bootcamp with a portfolio of seven projects that will show employers you’re worth the hire.
Get Career Support
Until You Get a Job
Personalized career support? Check. Connections to world-class employers? Double check.
Join a Community
of Data Professionals
Connect with a community of alumni who will become valuable resources in the field.
MODULE 1 -
MODULE 2 -
MODULE 3 -
MODULE 4 -
MODULE 5 -
MODULE 6 -
MODULE 7 -
UNIT 1: Exploratory Data Analysis Basics
Grow your knowledge of fundamental exploratory data analysis. This includes using programming languages like Python and SQL.
Unit 2: Exploratory Data Analysis Advanced
We’ll expand on unit one, diving deeper into Take your EDA learnings a step further by learning advanced methods for SQL and Python.
Project Due:
Your project will involve extracting insights from a messy dataset, writing code in Jupyter notebooks, performing exploratory data analysis using Python, and visualizing results with Matplotlib packages. You’ll also work with a relational database to pull and clean data.
UNIT 1: Linear Regression Basics and Web Scraping
We’ll teach you how to web scrape. Plus, we’ll cover the basics of feature engineering, cross validation, and linear regressions.
Unit 2: Linear Regression Advanced
Discover advanced linear regression methods, including regularization and stochastic gradient descent. Plus, become familiar with time series regression methods.
Project Due:
Show off your new skills by solving a linear regression problem. You’ll gather data through web scraping, go deep into regression theory, and practice using python modules such as scikit-learn. You’ll show your ability to apply foundational machine learning techniques like feature engineering and validation.
UNIT 1: Business Analysis
We’ll show you how to leverage data visualization best practices and spreadsheet tools for data analysis.
Unit 2: Presentations, Project Management and Ethics
Explore expert techniques for presentations, project management basics, and the ethical complexities of working with data.
Project Due:
You’ll choose a business problem to solve using data in a practical, ethical way. This will involve the application of iterative design techniques and project management practices. You’ll also explore, describe, and extract insights from tabular data sets in addition to building interactive dashboards for that data.
UNIT 1: Classification Basics
In unit seven, you’ll explore the basics of classification models and metrics, as well as feature engineering for classification problems.
Unit 2: Classification Advanced
Next, you’ll expand your classification knowledge by working with imbalanced datasets.
Project Due:
Show off your just-learned skills by solving a classification problem. You’ll use algorithms like KNN, logistic regression, decision trees, gradients boosting and more. Then, you’ll dive deeper into the concepts and techniques for supervised machine learning, address the challenges involving class imbalance, and determine the metrics used for your modeling problem.
UNIT 1: Natural Language Processing and Unsupervised Learning Basics
Explore the NLP basics, recommendation systems, and dimensionality reduction. Then, we’ll introduce you to techniques used for basic clustering.
Unit 2: Natural Language Processing and Unsupervised Learning Advanced
Learn and apply NLP techniques and advanced algorithms for clustering.
Project Due:
This project will involve text data analysis using NLP algorithms. You’ll use different techniques for dimensionality reduction like Principal Component Analysis, apply topic models like Latent Dirichlet Allocation and clustering algorithms like K-means.
UNIT 1: Neural Networks, Embeddings and Convolutional Neural Networks
Learn the basics of deep learning and neural networks. This includes transfer learning, embeddings, and convolutional neural networks.
Unit 2: Sequence Modeling
We’ll explore methods for modeling sequential data and deep learning.
Project Due:
You’ll select a problem related to text, time series, images, or other complicated data formats, and train your models or apply transfer learning techniques. This is your opportunity to show that you can solve data science problems using deep learning algorithms.
UNIT 1: Advanced Coding and Cloud Computing
Learn how to use advanced database tools, advanced programming techniques, web application deployment, and cloud computing.
Unit 2: Big Data
Learn how to use big data handling techniques and tools.
Project Due:
You’ll show that you can develop a modularized data processing pipeline, implementing tools like relational and non-relational databases, big data handling tools, cloud computing, and web application deployment.
Get a deeply focused learning experience, with a full-time format and engaging lectures.
Study on your own schedule with on-demand lessons and dedicated 1:1 instructor support. Assignment deadlines help hold you accountable.
Length
Tuition
Scholarship
Weekly Time Commitment
Schedule
Lectures
Instructors
Office Hours
Instructor 1:1s
Projects
Project Presentations
Career Support
Social Activities
Live Online
14 weeks
$18,500
$3,000
35-40 hours/week
Mon-Fri; 11am-6pm ET
Live Online
Metis Data Scientists
Weekly
Weekly
7
Live Online
Until Hired
Live Online
Online Flex
28 weeks
$9,800 $14,000
$3,000
15-20 hours/week
Flexible with deadlines to keep you on track
On-Demand
Metis Data Scientists
Weekly
Weekly
7
Live Online
Until Hired
Live Online
During Bootcamp
ONE-ON-ONE GUIDANCE
Map out your target salary, industry, job location and company with help from a career advisor.
SPEAKER SERIES
Throughout the program, you’ll hear from industry experts as they give advice and share experiences.
JOB SEARCH TUTORIALS
These instructional videos show you how to draft a strong resume, build an online presence, network, and more.
The Week After Bootcamp
WORKSHOPS
Pick up networking tips, prep for interviews, craft a stand-out resume, and more.
MOCK INTERVIEWS
Get technical and non-technical interview practice and feedback from experts who know what it takes to get hired.
Until You’re Hired
GRADUATE DIRECTORY
Be added to our graduate directory where hiring managers can see your portfolio, resume, and bio.
CONTINUED SUPPORT
Get customized career support until you get a job, and use our Alumni Portal to find your next opportunity.
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 to the Data Science & Machine Learning 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 our Data Science & Machine Learning Engineering Bootcamp consist of?
14 weeks of real-time classes (Live Online) or on-your-time modules over 28 weeks (Online Flex)
7 data science projects you can add to your portfolio
Personalized support from instructors and TAs
Career support during program and beyond
And a lot more
Bootcamp modules are offered as short, immersive courses. It’s a great option for those who are interested in a specific topic or anyone who wants to get a feel for the full bootcamp.
