FIU Data Science Bootcamp Application Deadline is Oct. 3 - Apply Now


Accelerate Your Career in One of the Fastest-Growing Fields

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.

Bootcamp Curriculum at a Glance


Exploratory Data Analysis


Linear Regression & Web Scraping


Business Fundamentals for Data Practitioners


Machine Learning Classification


NLP & Unsupervised Learning


Deep Learning Fundamentals


Introduction to Data Engineering

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.

Program Benefits

Our project-oriented, career-driven approach will take you to places you never thought you could go.



Study on your own schedule with on-demand lessons and dedicated 1:1 instructor support. Assignment deadlines help hold you accountable.


Weekly Time Commitment




Office Hours

Instructor 1:1s


Project Presentations

Career Support

Get a Feel For Our Online Flex Programs

Online Flex

Study on your own time with pre-recorded lectures.

Stay engaged and follow along as your instructor shares a presentation.

Be held accountable by assignment deadlines, and stay on track with structured subject modules.

Join the conversation on video, in the chat, and with the polling feature.

Take your learning further with assessments designed by Metis’s in-house team.

We simulate the in-person learning experience with a digital whiteboard.

Set up 1:1 time with your instructor, or connect with your peers via Slack and the online platform.

You’ll collaborate with your classmates during project work and pair-programming.

Watch presentations from invited speakers, take part in social events, and more.

Keep up with your teachers and classmates in your dedicated Slack channel.

Say Hello to Some of the Metis Instructors

The Data Science & Machine Learning Bootcamp is taught by data scientists with deep industry experience and online teaching expertise.
  • Rita Biagioli

    Data Scientist

Meet the Full Team

Career Guidance and Support Until You’re Hired

Industry-experienced career advisors work with you throughout the Data Science and Machine Learning Bootcamp and after graduation until you land a job.

During Bootcamp


Map out your target salary, industry, job location and company with help from a career advisor.


Throughout the program, you’ll hear from industry experts as they give advice and share experiences.


These instructional videos show you how to draft a strong resume, build an online presence, network, and more.

The Week After Bootcamp


Pick up networking tips, prep for interviews, craft a stand-out resume, and more.


Get technical and non-technical interview practice and feedback from experts who know what it takes to get hired.

Until You’re Hired


Be added to our graduate directory where hiring managers can see your portfolio, resume, and bio.


Get customized career support until you get a job, and use our Alumni Portal to find your next opportunity.

Join Other Metis Grads at these Top Companies

Meet Our Alumni

The Metis alumni network has more than 1,200 international data professionals. Read some of their stories to get inspired about your upcoming career change.


Machine Learning Engineer, Quora

Winter 2019

Read their story


Lead Product Scientist, Indeed

Fall 2017

Read their story | Watch Video


Data Scientist, DigitalGlobe

Summer 2016

Read their story


Data Scientist, Change Healthcase

Spring 2016

Read their story


Machine Learning Scientist,

Winter 2019

Read their story

One Hour at Bootcamp: Intro to Machine Learning


One Hour at Bootcamp: Intro to Machine Learning

During this recorded workshop, Joe Eddy, Senior Data Scientist and instructor here at Metis, provides you with a roadmap of the most important definitions and applications of machine learning.




  • What is the admissions process like? And who can apply to the

    Data Science and Machine Learning Bootcamp?

    We’re able to accept applicants for the Data Science and Machine Learning Bootcamp from the following U.S. states. If you currently reside in a state where we don’t yet have approval, you can still submit your application and our Admissions team will follow up with you once they have updates regarding your eligibility. 

    To complete the application process, each applicant must complete the following steps: 1) submit an online application, 2) complete a non-technical interview with the Admissions team, and 3) complete the technical assessment.

    At each of these three stages, our admissions committee reviews your application and determines your preparedness to succeed. We assess applicants on (1) programming experience, (2) math experience, (3) communication skills, (4) personality traits of curiosity, grit, and passion, (5) motivation to join the bootcamp and (6) potential overall fit within Metis. If the committee agrees that the applicant has the potential for success, the applicant is informed in writing of their acceptance within 2 business days of completing the technical assessment.

    Ready to apply? Get started here.

  • How can I prepare for the bootcamp (especially if I don’t feel ready quite yet!)

    If you’d like to enhance your Python, math, and general data science skills prior to applying, we’d recommend considering one of our part-time bootcamp prep courses. During, you’ll gain the skills you need to succeed in the Data Science and Machine Learning Bootcamp. You’re also able to  apply the tuition paid from one prep course towards the bootcamp.

    Additionally, we recommend that you register for our free Metis Admissions Prep to enhance  your data science skills, test your knowledge, and discover your next best step.

  • Is this a full-time commitment?

    Our Online Flex bootcamp has a flexible schedule requiring a weekly commitment of 15-20 hours and includes deadlines for assignments and projects to help you stay on track.

  • What are the payment options for the bootcamp?

    Tuition for the Data Science and Machine Learning Bootcamp is $14,000. If accepted, a deposit of $1,500 is required within 7 days of signing the enrollment agreement in order to secure a spot. After making the deposit, students have the option of paying in installments. For affordable financing options, we partner with third party financing partners Climb Credit and Ascent.  Both offer several monthly repayment options for our students accepted to the bootcamp. 

    Women, members of the LGBTQ community, members of underrepresented demographic groups*, and/or veterans or members of the U.S. military are eligible to receive a $3,000 scholarship toward their Data Science and Machine Learning Bootcamp tuition.

    *Underrepresented demographic groups include African Americans, Mexican-Americans, Native Americans (American Indians, Alaska Natives, and Native Hawaiians), Hispanic and Latino Americans, Pacific Islanders, and mainland Puerto Ricans.

  • How do Metis Career Services help me find a job?

    Since launching our bootcamps in 2014, our Career Services team has helped graduates find employment in cities and states all over the U.S. and the globe. Our team of Career Advisors are committed to:

    • - Coach you through this career transition through one-on-one meetings, workshops focused on job readiness, and helping you make valuable  connections to our always-growing alumni network.
    • - Expose graduates to our hiring network, filled with employers looking to hire data science professionals.
    • - Provide post-bootcamp support and professional development through our until you’re hired.


Read our FAQs

Not Ready to Commit?

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.

Explore Courses