MS in Computational Data Science Admission Criteria
Students are expected to have experience in programming, software engineering, algorithms, and background in statistics. Competence in these areas is defined by the following UCR undergraduate courses (or equivalents; for course descriptions see the UCR General Catalog https://registrar.ucr.edu/registering/catalog ):
- 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.
Applicants must submit scores from the Graduate Record Exam, General Test (GRE). Applicants whose first language is not English are required to submit scores from the TEST of English as a Foreign Language (TOEFL) or the International English Language Testing System (IELTS) unless they have a degree from an institution where English is the exclusive language of instruction. Additionally, each applicant must submit letters of recommendation, as per the admission requirements. All other application requirements are specified in the graduate application.