Silicon Valley Data Academy

Data Scientists Born Here
“Data Scientist. The Sexiest Job of the
21st Century”
-Harvard Business Review

About Svda

8 week immersive training program to become an enterprise class data scientist/engineer
Fellowship Program

Silicon Valley Data Academy offers full scholarship to our candidates accepted in our Fellows Program. 

Curriculum + Project Based Learning

SVDA certainly has a rigorous and comprehensive curriculum that will give you all the tools to be an enterprise class Data Scientist. However, the core of our instruction relies on giving you real world, practical problems and projects to catapult you from theoretical to practical data science.

Get Hired

 Work directly with over 20 top firms in the Bay Area and find the industry that excites you the most!

Origin

A Collaboration of Silicon Valley’s Finest

Silicon Valley Data Academy is designed to develop enterprise class Data Scientists. A collaboration of Silicon Valley Data Sciences and GSVlabs, our program operates out of GSVlabs which is the hub for global innovation and located right in the heart of the Silicon Valley. SVDA is powered by Silicon Valley Data Science which houses some of the leading data scientists in the world. Between our staff, our curriculum, our facilities, and our partners, SVDA has created the ultimate platform to land you your dream job as a data engineer.

SVDS has assembled elite data engineering and data science teams who specialize in data-driven product development and business transformation. Assisting leading corporations to develop and deploy high impact big data solutions. 
http://svds.com/

A global innovation center that focuses on four pillars of high growth, high impact verticals of Big Data, EdTech, Mobile, and Sustainability. GSVlabs supports 100+ Startups and corporate partners turning ideas into game changing enterprises.
http://gsvlabs.com/

the programs

 data engineering

“Torture the data, and it will confess to anything.”
-Ronald Coase, Nobel Laureate

The Data Engineering program is designed to teach engineers how to build and operate frameworks to handle the exploding amount of data being collected in today’s top firms . The curriculum is structured by feedback from industry leading companies on the practical skills needed to transition to a career in Big Data Engineering.

is it right for me?

Candidates come from an extensive background of CS programming and engineering. Candidates typically have completed their M.S/PhD in a related field or are currently doing Post Doctoral research. The rigorous curriculum is designed for fellows that already have a significant understanding of Java, statistics, and distributed systems.

8 week immersive

Week 1: Mastering Hadoop, Its Ecosystem, MapReduce, and Crunch
Week 2: Design Process and Web Scraping (project 1) 
Week 3: Databases, SQL, cleaning and maintaining data.
Week 4: Creating Data Products (project 2)
Week 5: Engineering Data Hubs and Data Lakes
Week 6: Getting value from data (main project)
Week 7: NoSQL, Cloud, Data Visualization, JavaScript essentials
Week 8: Special Big Data Topics

 Data science

(Applications currently closed)
“Data Scientist (noun): Person who is better at statistics than any software engineer and better at software engineering than any statistician.”
-Josh Wills, Cloudera

This intense program will let you solve real problems, for real companies. The curriculum is structured by feedback from industry leading companies on the practical skills needed to transition into a career in Data Science.

is it right for me?

Candidates come from an extensive background of math, quantitative statistics, and engineering. Candidates typically have completed their PhD in a related field or are currently doing Post Doctoral research. The rigorous curriculum is designed for fellows that already have a significant experience with large data sets, CS programming, and big picture problem solving.

8 week immersive

Applications for the Data Science program are currently closed. If you feel your programming knowledge is sufficient, do check out our Data Engineering program starting Oct 12th!

THE TEAM

Jesse Anderson – Lead Instructor 

When it comes to teaching Data Science, there is no one better than Jesse. For over 15 years Jesse has been the closest thing to a superhero in the Data world, creating and delivering curriculum for Cloudera, Couchbase, and numerous Universities.

John Akred – Senior Data Science Advisor

With over 15 years in advanced analytical applications and architecture, John is dedicated to helping organizations become more data-driven. He combines deep expertise in analytics and data science with business acumen and dynamic engineering leadership.

Stephen O’Sullivan – Senior Data Engineering Advisor

A leading expert on big data architecture and Hadoop, Stephen brings over 20 years of experience creating scalable, high-availability, data and applications solutions. A veteran of WalmartLabs, Sun and Yahoo!, Stephen leads data architecture and infrastructure.

Blaise Johnson – Director

Blaise has managed a multitude of teams all over the globe. After graduating from Stanford, he has become immersed in the tech industry and has led teams of all sizes from the Silicon Valley all the way to Sydney, Australia. As Director, Blaise will be the main point of contact for any and all inquiries about SVDA. Feel free to contact him at blaise@gsvlabs.com.

Edd Dumbill – Marketing and Strategy Advisor

Founder of the pioneering data conference, O'Reilly Strata, Edd is a respected voice in the worlds of data, open source and the web. Bringing together deep technical know-how with market understanding, Edd makes sense of information technology and its trajectory.

So you have the gift of beautifully articulating complex syntax and know everything there is to know about Data Science? Become a mentor and transfer your knowledge to the future innovators of the world! Contact us with your resume if you are interested.

THE Working environment

Community Space
Classroom
Gym

Silicon Valley Data Academy is located right in the heart of the Bay Area. We are fortunate to operate out of the leading global hub of technology at GSVlabs. GSVlabs is a dynamic, fast paced, and cutting edge 72,000sqft work space that houses over 100 thriving startups. As an SVDA Fellow, you will have access to all of GSVlabs’ amenities including a gym, yoga studio, green screen studio, billiards/ping pong tables, courtyards, basketball/volleyball hoops –– everything you need to enjoy the California weather. Not to mention working in the same community with some of the brightest minds in the industry. 

GSVlabs has become a home to some of the most prominent people in the Silicon Valley. We regularly host speaking sessions from innovators like Guy Kawasaki, Peter Thiel, Bill Campbell, Ronnie Lot, Ron Johnson, and many more!

Partners

Work directly with the top companies in the Bay Area. Over the course of the program you will have a chance to receive guest lectures, info sessions, mentoring, and take field trips to over 20+ dream companies in the Silicon Valley.
Interested in partnering with SVDA? Contact us Here to get engaged with the world’s brightest future Data Scientists

faq

Easy answers to the most commonly asked questions
What prerequisites are necessary to become a Fellow?

Silicon Valley Data Academy is designed for those that already have extensive backgrounds in programming and distributed databases. The goal of our program is not to teach you how to code, but teach you how to apply your code in a meaningful and efficient way to get the most out of your data. You should already be familiar with Java, Python, and databases.

What is the difference between the Data Engineering and Data Science programs?

Did you love playing with legos as a kid? Were you the one that was dying to take apart and rebuild every toy you got for Christmas? The Data Engineering program is probably for you.

Data Engineering has a premium focus on programming. The Data Engineering Program focuses on building and designing the framework to collect data. Mostly students with a very strong background in CS will thrive in the Data Engineering program. 

Were you always the banker while playing Monopoly? Were you constantly coming up with equations that would yield funny words when you turned your calculator upside down? The Data Science program is for you.

The Data Science program is geared towards those with an extensive background in Statistics and dealing with large data sets. While some programming background is necessary, it is not as intensive as the Data Engineering track. The Data Science program will expect you to have some prior knowledge of R and Python, as those languages will be taught in the curriculum.

What prerequisites are necessary to become a Fellow?

Silicon Valley Data Academy is designed for those that already have extensive backgrounds in programming and distributed databases. The goal of our program is not to teach you how to code, but teach you how to apply your code in a meaningful and efficient way to get the most out of your data. You should already be familiar with Java, Python, and distributed databases. 

What are collaborating companies?

Our collaborating companies serve a very important role to our programs. Top data scientists from industry leading companies will regularly be stopping by for guest lectures, speaking sessions, recruiting, and most importantly they will provide real world projects to give you a real life, practical insight to what it is like to work as a practicing data scientist at a leading firm. All collaborating companies will also play a large role in the recruitment facet of the company. Hear first hand exactly what top companies look for in a rock star data scientist, and find a job working in the industry that excites you the most.

What is the day to day of the program?

Each day of the program will be unique and is designed to simulate the lifestyle of a practicing data scientist. The program will consist of the following:

Curriculum: The first portion of the program will be heavily focused on our curriculum that is designed to give you all the tools you will need to become a rock star data scientist. Code review in the morning, lectures in the afternoon, followed by homework and projects to apply the day’s curriculum to real world problems.

Guest Lectures: SVDA will regularly bring in the Bay Area’s top data scientists to give you insight to their industry needs. Not only will they teach you the invaluable skills they have learned in their tenure, but they will also let you know what it takes to be a successful data scientist in their field.

Field Trips: The day to day at SVDA is going to be a grind, we can assure you of that. To get a break from the rigorous course, we will be taking Fellows on field trips to the HQ of our collaborating companies. Get up close and engaged with different companies in the Bay Area to both see the amazing technologies they are working on, and also get a feel for the fun and exciting Silicon Valley culture that each company has embraced.

Projects: The problem with academia is that you don’t get an opportunity to use your skills on real world, practical projects. At SVDA you will receive real projects, from real companies so that you can both apply and showcase your skills.

How does the recruiting work?

The Bay Area is starving for good data scientists. At SVDA you will engage with the best companies in the world that are searching for data scientists/engineers. After working on their projects, engaging with them during QA sessions, and participating in our recruiting events, we are confident that you will find your future employer.

What will I learn at the Academy?

Our curriculum is designed by the best data scientists in the world. We have painstakingly taken feedback from all of the top companies in the world about what they want to see in a data scientist/engineer and have applied that feedback to our curriculum. Throughout the curriculum you will learn:

Data Visualization
Data Mining
Statistics
Machine Learning
Cutting edge tools like Spark and Kafka
Databases and parallelization using Hadoop, Spark, Hive, MapReduce, NoSQL
Natural language processing