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 ‘related theories’ and being able to ‘make it work’ are not the same. And, in areas as important as Artificial Intelligence, Data Science, and Machine Learning, if we collectively cannot actually implement and create, then we'll reduce our competitive advantage, economic strength, and even national/global security.

The Data-X framework is designed to bridge the gap between theory and practice as well as academia and industry, by exposing students to state-of-the-art implementation techniques and mindsets.

This highly-applied course surveys a variety of key concepts and tools that are useful for designing and building data science, AI, and Machine Learning applications and systems. The course introduces modern, open source computer programming tools, libraries, and code samples that can be used to implement data applications. The mathematical concepts highlighted in this course include filtering, prediction, classification, decision-making, LTI systems, spectral analysis, and frameworks for learning from data. Each math concept is linked to implementation using Python libraries like NumPy for math array functions, Pandas for manipulation of tables, Scikit-learn for machine learning modeling, Tensorflow and Keras for deep learning, and many other topics related to NLP, Neural Networks, Recommender Systems etc.

Prerequisites

Students from all majors, both undergraduate and graduate are welcome; however, due to the technical nature of this class, students must have the ability to write code in Python, and have taken a probability or statistics course.

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 and the IT World Award 2018. He was AI Product Director at Bill.com and recently left to explore a greater challenge in AI and/or entrepreneurship. 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.