MS in Computational Data Science

University of California, Riverside (Engineering)

All applicants to the MS in Computational Data Science program must have completed a Bachelors degree or its approved equivalent from an accredited institution and to have attained undergraduate record that satisfies the standards established by the Graduate Division and University Graduate Council.

Students are expected to have experience in programming, software engineering, algorithms, and background in statistics.

CS 141 - Intermediate Data Structures and Algorithms

CS 100 - Software Construction

MATH 010A - Multivariable Calculus

MATH 031 - Linear Algebra

A course covering foundations of probability and statistics (such as STAT 155 - Probability and Statistics for Science and Engineering, or, EE 114 - Probability, Random Variables, and Random Processes in Electrical and Computer Engineering)

Applicants may be admitted with course deficiencies, provided they take remedial steps to cover the deficiencies. All such remedial work cannot be counted towards the MS degree requirements and should be completed within the first year of graduate study, and in all cases the deficiency(s) must be corrected BEFORE a student can enroll in any graduate course from the same specialty area. The details will be decided by the Graduate Advisor of the program in consultation with the student. The CSE department also offers a sequence of ‘Bridge summer courses that can be used as a first step by students who lack basic undergraduate background in programming, algorithms and data structures.

English Language Requirement

TOEFL

• Interned-Based (iBT) - 80
• Home Version (iBT) – 80
• Paper-Based test (PBT) – 550

IELTS - Minimum IELTS score: 7 overall total score; The minimum score in each individual component must be 6 or above