Applied Data Science with Venture Applications: Data-X

INDENG 135/235 (3 units)

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Class Description

Today, the world is literally reinventing itself with Data and AI. However, learning a set of ‚Äėrelated theories‚Äô vs. ‚Äėmaking it work‚Äô is not the same, especially for innovating competitive advantage, economic strength or social good, and even national/global security.

Thus, Data-X is a mixture of half Data Science and Data Systems and the other half on Innovation, which includes behaviors and processes required to create new data-related applications.  At its core, Data-X is an advanced project course which is highly applied.  The course surveys a variety of key theoretical concepts and software tools. Data-X has a focus on helping students validate, design, and build data science, AI, and Machine Learning applications and systems (not only algorithms) for real-world user impact.

The course covers 3 tracks aimed to guide students’ project work and future industry work: 

  • code and theory (e.g., high- and low-code tools),
  • broader insight from instructors, industry guests, and inductive learning games, and
  • teams and projects (e.g., live team demos and feedback).

To further enrich student learning experience, project teams will be assigned an external industry mentor for a few hours per month.

While the syllabus for next semester is subject to refinement, the Fall 2021 syllabus is public at https://datax.berkeley.edu/berkeley-course/.

Prerequisites

Students from all majors and countries are welcome since diversity adds value in co-building applications and systems to help society. However, the course has technical application, so students should have completed a probability or statistics course, and have the ability to write Python code (or be committed to complete foundational Python material by week 2 end):

More Information

View the Data-X website for more information including a syllabus, class material and previous projects.

Instructor

Ikhlaq Sidhu, Chief Scientist, and Faculty Director of UC Berkeley’s Sutardja Center for Entrepreneurship & Technology. He is the author of the book "Innovation Engineering" and he holds 75 patents in internet communication technologies. Dr. Sidhu developed the Entrepreneurship & Technology area at the #1 public university in the world, the Berkeley Method of Entrepreneurship (for new ventures), and the Berkeley Method of Innovation Leadership (for technical leaders). In 2018, Sidhu received the IEEE Major Education Innovation Award. He received Berkeley IEOR Emerging Area Professor Award in 2009 at UC Berkeley. In 1999, he received 3Com Corporation’s Inventor of the Year Award. He serves on many advisory boards. He received his bachelor’s degree in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign, and his masters’ degree and doctorate in Electrical Engineering from Northwestern University.

 

Derek S. Chan enjoys learning from and empowering people through education, technology innovation, and theater arts. His Artificial Intelligence (AI) teams and products have helped companies reach their highest-ever customer satisfaction and/or revenue growth, plus #1 AP Automation 2020-21 and the IT World Award 2018. He was AI Product Director at Bill.com and now explores greater personal challenge and meaning through his own startup. He is an invited speaker at AI conferences, and an alum of UC Berkeley’s Master of Information and Data Science program, co-receiving the Hal R. Varian Award followed by an informal Google partnership.

 

Refer to our Courses page for a full list of SCET courses and current class offerings

and our Certificate page for more information on our Certificate in Entrepreneurship & Technology.

Contact

Contact SCET Academic Program Manager Michelle Lee at lee.2293@berkeley.edu for additional questions.