Large-Scale Social and Complex Networks: Design and Algorithms

EC ENGR XLC 232E

This course is part of the UCLA Henry Samueli School of Engineering and Applied Science (HSSEAS) Master of Science in Engineering Online (MSOL) program.  It is available only to students pre-approved by HSSEAS. For more information visit msol.ucla.edu. 

READ MORE ABOUT THIS COURSE

About this course:

EC ENGR 232E “Large-Scale Social and Complex Networks: Design and Algorithms” (Prof. Roychowdhury, V.) Lecture, four hours; discussion, one hour; outside study, seven hours. Introduction of variety of scalable data modeling tools, both predictive and causal, from different disciplines. Topics include supervised and unsupervised data modeling tools from machine learning, such as support vector machines, different regression engines, different types of regularization and kernel techniques, deep learning, and Bayesian graphical models. Emphasis on techniques to evaluate relative performance of different methods and their applicability. Includes computer projects that explore entire data analysis and modeling cycle: collecting and cleaning large-scale data, deriving predictive and causal models, and evaluating performance of different models.

Contact Us

Our team members are here to help. Hours: Mon-Fri, 8am-5pm
Ready to start
your future?
By signing up, you agree to UCLA Extension’s Privacy Policy.

vector icon of building

Corporate Education

Learn how we can help your organization meet its professional development goals and corporate training needs.

Learn More

vector icon of building

Donate to UCLA Extension

Support our many efforts to reach communities in need.

Innovation Programs

Student Scholarships

Lifelong Learning

See More