Online Data Science

Reinvent your career with our online data science immersive workshop.

Get Started for Free


Online But Not Alone

Our online Data Science bootcamp takes 21K Skills + Galvanize’s industry-tested curriculum, schedule, and makes it available wherever you call home. You'll learn from instructors face-to-face over state-of-the-art conferencing software, pair program with classmates almost every day of the course, and have the option to socialize during special after-hours events. This is a live course with a rigid schedule and is not self-paced.

Learn Alongside the Brightest Minds

Our highly motivated students come from a variety of backgrounds like data analysis, engineering, and mathematics. You’ll learn to code alongside a cohort of driven peers and develop meaningful connections with our world-renowned faculty and career services team, who come together to help you identify strengths, define goals, and connect you to our 2,250+ hiring partners.

Learn from Expert Data Science Bootcamp Instructors

Our team of experienced, full-time instructional faculty utilize real-world case studies to teach best practices in statistical analysis, machine learning, natural language processing and data visualization that will prepare you for a successful career in Data Science.

View Instructors

Learning Experience

Submit Application

Apply for the course for free to get access to an online pre-assessment test & preparation material. Based on your prior expertise you may require anywhere between 0-6 weeks to finish the study material provided to you. The study material is provided free of cost and is for the purpose of getting you prepared for the course.


Little or no exposure to programming and higher-level mathematics (Calculus, Statistics, Probability). Could be a teacher, musician, lawyer, analyst working in data, or a naturally curious person. If you fall in this category we suggest you go over all the prep material to pass the pre-assessment test. This may take anywhere between 3-10 weeks.

Intermediate Python, No Math or with Math, No Python

Strong at programming in Python but needs to solidify Applied Mathematics fundamentals. Might be an analyst or an engineer with less mathematical experience.

Strong math skills but needs to learn Python. Might have an advanced degree from a quantitative field (economics, math, biology, oil & gas). If you fall in either of the category you will need anywhere between 2-5 weeks to go over the prep material in order to pass the pre-assessment test.


Experienced programmers with strong mathematical training. Might have a PhD from a quantitative field who programmed during their study, maybe not in Python (Statistics or Physics), or Computer Science majors who have worked as software engineers. If you fall in this category you can proceed to the pre-assessment test.

Pre Course Work

The pre- course work material will only be shared with the candidates who wish to continue with the program and have successfully cleared the pre-assessment test. For those who wish to take up the program but have not cleared the pre-assessment test, you have the option of taking the test again.

Data Science Immersive

The 12 week program begins for all qualified students. For the full time course we suggest you put in 6-8 hours a day to successfully graduate from the program.


Quarter 1: Python and Statistics Fundamentals

Students jump right into a Python-based curriculum and explore and learn statistical analysis, including frequentist and Bayesian methods. Students master fundamental data science concepts while growing in skill with libraries like numpy, scipy, and pandas. For those who need to learn Python basics, we offer an in-person Python Fundamentals course.

Quarter 2: Machine Learning & Prediction

In the second quarter, we dive into machine learning, working on real problems in classification, regression, and clustering using structured and unstructured data sets. We build a conceptual understanding of each model before practicing with libraries used in the industry.

Quarter 3: Natural Language Processing & Recommenders

Students learn natural-language processing, recommender systems, neural networks, and time-series data. We gain experience with big data and data in the cloud. By the end of this section, students are well-versed in data science and ready to work independently.

Quarter 4: Capstone Projects & Case Studies

Students work independently on three projects unique to their interests or career aspirations. These "capstone projects" solve real problems using the technical skills students have learned throughout the course. Students also work on several group case studies throughout the program, combining real-world data with what they've learned each week while practicing team-based software development.

Admission Process

Begin Application

Study Prep Material

Give the Pre-Assessment Test

Pay Tuition & Download Pre-Course work material

Begin Program

What our alumni think

Eric Levin

“The curriculum seems to be perfectly formed... with short, interactive lectures followed by immediately heading over to our workstations and implementing assignments based on the content we just learned.”

Austin Krauss

“I wouldn't be where I am today without Galvanize. I started my journey with little experience in data science, but I emerged from the program within multiple job offers in the field.”

Puneet Lahoty

“The community of Galvanize was hands-down the best part of the experience. The immersive program trained me to develop grit & a strong work ethic that eventually led me to quickly landing a new job!”

Who Has Hired Our Data Science Students

Admission & Fees

Flexible financing & EMI Options takes the worry out of tuition

What’s stopping you from transforming your career and earning a higher salary? If it’s the cost of tuition, it’s time to consider 21K Skills. After a small down payment, our industry-best EMI options allow you to pay your course fee in 12 or 24 months. Start earning before you pay us the full tuition!

View Plans

Ready to change your future?

Get Started for Free