Become a Data Scientist

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$114K Average Starting Salary

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75+ Alumni Employers

94% Placement Rate

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Ready to learn Data Science?

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Teaching Tomorrow’s Data Scientists

In just 12 weeks, you'll learn the tools, techniques, and fundamental concepts you need to know to make an impact as a data scientist. During the course of the program, you'll work through messy, real-world data sets to gain experience across the data science stack: data munging, exploration, modeling, validation, visualization, and communication.


After graduating from the Data Science program, many of our alumni pursue direct data scientist roles, while others pursue roles in machine learning, software engineering, data analysis, data science consulting, and data product management. Throughout the Galvanize program, students have the opportunity to explore these career paths and engage with professionals working in the field, as well as potential employers.

Where our Graduates Work

After leaving Galvanize, our students go on to work at some of the most exciting and innovative tech companies all across the country. Here are just a few of them:

Our Instructors

Giovanna Thron

Giovanna Thron
Lead Instructor | San Francisco – SoMa, Seattle – Pioneer Square

Isaac Laughlin

Isaac Laughlin
Instructor | San Francisco – SoMa

Brian Mann

Brian Mann
Associate Instructor | Seattle – Pioneer Square

Giovanna Thron

Joshua Bernhard
Instructor | Denver – Platte

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I had the opportunity to spend three months just focusing on learning surrounded by other crazy-talented people.

– Erin Burnside, Graduate & Data Scientist at Asana


Grounded in Python, our program covers all the necessary tools and concepts used by data scientists in industry, including machine learning, statistical inference, and working with data at scale. As you learn more advanced techniques, you’ll use tools like SQL and NoSQL. When you graduate, you’ll have a solid grasp of machine learning, statistics, and will have built numerous data science applications.

Python & SQL


Machine Learning

Big Data


Week 1 - Exploratory Data Analysis and Software Engineering Best Practices
Week 2 - Statistical Inference, Bayesian Methods, A/B Testing, Multi-Armed Bandit
Week 3 - Regression, Regularization, Gradient Descent
Week 4 - Supervised Machine Learning: Classification, Validation, Ensemble Methods
Week 5 - Clustering, Topic Modeling (NMF, LDA), NLP
Week 6 - Network Analysis, Matrix Factorization, and Time Series
Week 7 - Hadoop, Hive, and MapReduce
Week 8 - Data Visualization with D3.js, Data Products, and Fraud Detection Case Study
Weeks 9-10 - Capstone Projects
Week 12 - Onsite Interviews


As part of our curriculum, you’ll work on individual and group projects, which includes a personal capstone project that you’ll present at demo nights and hiring events. You'll also have the opportunity to work with real tech companies to put your new-found skills to work. Here are just a few awesome things our students have built:

Early-Detection of Forest-Fires
Sean Sall

Accurately identify fires so that the detected fires data set can be used in near real-time to aid forest fire prevention, where every minute counts.

Yelp Summarization Miner
Jeff Fossett

Aspect-based sentiment analysis of online reviews
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Wini Tran

Predicting emerging artists from HypeM's Latest Blogged Artists

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The Language of Fraud
Jana Thompson

Project built using natural language processing technologies and tools such as Stanford, Core Parser Word2Vec, and CoreNLP to predict fraudulent behavior online.


We’ll give you a take home assignment to assess your quantitative and programming skills, then conduct two technical interviews. The first evaluates your proficiency with programming in Python while the second covers probability, statistics, experiment design, and basic modeling. We look for students who are familiar with data analysis tools and practices and a background in a quantitative disciplines like foundational statistics, probability, linear algebra, or mathematics.

Scholarships and Financial Aid

We offer partial scholarships based on merit, demonstrated financial need, and increasing participation in technology among underrepresented groups such as women, veterans, minorities, and people who identify as LGBT. We also partner with Skills Fund for students who need help financing their tuition.

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Campus Life

At our campuses, diversity and collaboration are the norm: developers, data scientists, and community members learn from each other and work collaboratively. With expert instructors, startups, and industry partners working side by side, there’s always someone to help you get unstuck, offer you new challenges, or provide a key introduction.

Career Preparation

Learn data science by doing data science. Our curriculum is designed around solving practical, real-world problems with relevant data sets. After completing your 3-week capstone project, you’ll work with our outcomes team to receive interview coaching and practice, resume review, and get introductions to partner companies to ensure you put your best foot forward after graduation. Present your project and interview with 30+ companies at our Hiring Day.

Have More Questions?

Read our full FAQ or get in touch with someone on the Galvanize team.

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Upcoming Dates

San Francisco


Aug 01 - Oct 28

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2nd Street District

Aug 22 - Nov 18

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Aug 29 - Nov 25

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Pioneer Square

Sep 05 - Dec 02

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San Francisco


Sep 12 - Dec 09

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