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. During and after graduation, you'll receive career support and advisors will help you perfect your resume and interviewing skills.

Career Transformation Happens Here

We won’t just teach you sought-after machine learning skills. We’ll equip you with an impressive portfolio and career support.

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.

Career Support During
and After Bootcamp

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.

Data Science & Machine Learning


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

Career Guidance and Support

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


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.


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.


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


Get customized career support and use our Alumni Portal to find your next opportunity.