Learn Data Science San Francisco

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$111K Average Starting Salary

2014-2015 Placement Data

75+ Alumni Employers

92% Placement Rate

2014-2015 Placement Data

Ready to learn Data Science in San Francisco?

Apply for one of our upcoming courses.

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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

Ryan Henning

Ryan Henning
Lead Instructor | Austin - 2nd Street

Isaac Laughlin

Isaac Laughlin
Instructor | San Francisco – SoMa

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, including a personal capstone project through which you'll showcase how you apply your new technical skillet to solving real business problems. Here are just a few awesome things our students have built:

Mijail Gomez

A human facial expression classifier using Deep Neural Networks; finds and classifies faces as: happy, sad, surprise, fear, anger and neutral.

Brew Hound
Skylar Versage

A micro brewery recommender system; Are you traveling and want to know a good micro brewery to visit? Use this handy website to get the best local micro brewery recommendation!

Scott Contri

Discover your writing style; Stylish will tell you which authors you are most similar to.

Charles Lynn

Dog breed classifier using Deep Neural Networks; Want to know what kind of dog you are? Well, plug your photo into this website.


We’ll give you 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: data scientists, engineers, and data analysts learn from each other and work together. With expert instructors, startups, and industry partners working side by side, there’s always someone to help you get unstuck or offer you new challenges to put your skills to the test.

Career Preparation

You will work with a Career Services Manager in the city in which you attended the program. They will help you identify your strengths and career interests, help you refine your career goals, and identify opportunities for you to connect with hiring partners. Working in tandem with each of our Career Services Managers is a Partnerships Relations Manager, dedicated to identifying, cultivating, and developing regional and national employer relationships for you and all of our Galvanize students.

Have More Questions?

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

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Upcoming Dates