Data Science Engineering

Data Science Engineering Program

UPON APPLYING, PLEASE SELECT “ENGINEERING – ONLINE” AS THE MAJOR.  THEREAFTER, YOU WILL BE ABLE TO SELECT DATA SCIENCE ENGINEERING AS A SPECIALIZATION.

Degree: Master of Science in Engineering With Certificate of Specialization in Data Science Engineering

Area Directors: Prof. John Cho  & Prof. Vwani P. Roychowdhury 

Description:
The exponential growth of data generated by machines and humans present unprecedented challenges and opportunities. From the analysis of this “big data”, businesses can learn key insights about their customers to make informed business decisions. Scientists can discover previously unknown patterns hidden deep inside the mountains of data. In this program, students will learn key techniques used to design and build big data systems and gain familiarity with data-mining and machine-learning techniques that are the foundations behind successful information search, predictive analysis, smart personalization, and many other technology-based solutions to important problems in business and science.

Degree Requirements: At least nine courses are required (36 Units), 4 core courses in Data Science Engineering + 4-5 courses in a technical domain, and meet Comprehensive Exam Requirement. Please see comprehensive requirements below:

Fundamental Courses in Data Science Engineering : Core Courses: Select 4 courses from the following list:

COM SCI 143 Database Systems OR COM SCI 240A Databases and Knowledge Bases

COM SCI 249 Big Data Analytics OR EC ENGR 205A Matrix Analysis for Scientists and Engineers

COM SCI 260 Machine Learning Algorithms OR EC ENGR 210A Adaptation and Learning 

EC ENGR 219 Large-Scale Data Mining: Models and Algorithms OR EC ENGR 235A Mathematical Foundations of Data Storage Systems

EC ENGR 232E Large Scale Social and Complex Networks: Design and Algorithms *New core course beginning Summer 2018*

The remaining electives can be selected:

EC ENGR 131A Probability and Statistics

EC ENGR M214A Digital Speech Processing

EC ENGR 214B Advanced Topics in Speech Processing

EC ENGR 235A Mathematical Foundations of Data Storage Systems

COM SCI 249 Big Data Analytics 

COM SCI 260 Machine Learning Algorithms 

COM SCI 262A Learning and Reasoning with Bayesian Networks 

COM SCI 249 Big Data Systems 

COM SCI 246 Web Information Systems

Comprehensive Exam Requirement

Students can meet the Comprehensive Exam Requirement in two ways: Choose (1 option below)

Option 1:

Take and Pass ENGR 299 Capstone Project course.

Option 2:

Take and pass three written exams for three different graduate level courses within the student’s area of specialization. The written exams are held concurrently with the final exam of the graduate level courses. Students may select which exams they would like to count towards the Comprehensive Exam requirement.

Electives:

As long as you have met the requirements above the remaining courses may be selected from  other Engineering departments. No approval is necessary

Thesis Plan

NONE

Time-to-Degree

Students are expected to complete the degree within two academic years and one quarter, including two summer sessions. The maximum time allowed in this program is three academic years (nine quarters), excluding summer sessions.