Data Lab

Today, the world is literally reinventing itself with Data and AI.  The Data-in-Action Lab in the Sutardja Center at UC Berkeley exists to accurately understand the art for transforming today’s world with data in real life.

The approach of the lab is to bring together students, faculty, new ventures, and large firms because each of these segments provides an important part of the understanding of data problems to the other.  And as a result, we have the opportunity to develop a large-scale, holistic, data-related skill set. One that is capable of creating next generation of new data applications.

Key Factor 1: However, data science algorithms are just small part (say 1% of codebase) of any so-called smart application in real life today.  The full scope of todays applications include many other components including natural language input and output types, storage, cleaning, business logic, feedback loops, reliability, fault detection, risk management models, and much more.

Key Factor 2: Existing open source tools are becoming increasingly powerful.  Using tools together is an art which is still not fully understood.


Shomit Ghose

Industry Co-lead, Data in Action Lab
Industry Fellow, SCET

Ikhlaq Sidhu


Ken Singer

Managing Director, SCET

Jocelyn Weber

Industry Fellow, SCET, IEOR

Alexander Fred Ojala

Research Director

David Law

Industry Fellow, SCET, IEOR

Click HERE to visit Data-X Blog.

Noise Injection

Exploring New Methods to Enhance Data Privacy | Fall 2017

Data Science and Transnational Security

Developing Solutions to Increase the productivity of Experts Trying to Stay One Step Ahead of Criminals | Spring 2017

Featured Courses

Challenge Lab: Internet 3

Semesters offered: Fall 2017 (4 units)

INDENG 185 001

The web has come a long way—today, we have search engines that predict our searches, smart refrigerators ordering food, and virtual assistants giving us directions. But the convenience of user-centric technology has given birth to an evil twin—big data solutions that manipulate consumers, deceive voters and determine our credit ratings. In this class, you will be challenged to disrupt the biggest players on the Internet, from search engines to social networks. You will take on the role of a technology entrepreneur as you build real solutions and businesses that take on the biggest companies that abuse big data for their financial gain.

Applied Data Science with Venture Applications

Semesters offered: Fall & Spring (3 units)

INDENG 135 | INDENG 290-02

Data-X a technical course that teaches students to use foundational mathematical concepts and current computer science tools to create data-related applications and systems for real world problems. Computer science tools for this course include Python with NumPySciPypandasSQLNLTK, and TensorFlow. Math concepts include filters, prediction, classification, transforms, Bayesian, maximum likelihood, Markov state space, network graphs, and an introduction to deep learning.  The tools will be presented in applications common to data flow organization of Collect, Combine, Store, Use, Analyze, and Visualize.

Research Archive