Computer Science / Bachelor of Science to Master of Science in Data Science / Fast Track

Total Credit Hours: 128
Major Credit Hours:
53

The Computer and Mathematical Sciences Department offers a Bachelor’s to Master’s Fast Track option for Lewis University undergraduate Computer Science majors interested in the Master of Science in Data Science (MSDS). The Fast Track option allows qualified undergraduates to complete the MS in Data Science in less time than would be possible if the two programs were taken separately. Up to nine graduate hours may be used both to complete the Bachelor of Science degree (128 hours) and to satisfy specific course requirements in the Master’s program (36 hours). Students apply for admission to the Fast Track option by submitting both the department application form and the Block Tuition Exemption form to the Chair of the Computer and Mathematical Sciences Department when they reach senior status (complete 90 credits); have completed the following courses: CPSC 20000, CPSC 21000, CPSC 24500, MATH 24000, MATH 30700, and MATH 31000; and have achieved a minimum GPA of 3.0 in courses in the B.S. in Computer Science major. Qualified undergraduate students approved for the Fast Track option may apply financial aid to one, two, or three graduate courses and are exempt from the 18-hour block in the semesters when they take these select graduate courses. Students who take nine credit hours of selected graduate courses in the MSDS curriculum in their senior year and earn a grade of “B” or better in each of those courses will have to complete a minimum of 27 more credit hours to earn the MSDS. Students accepted into this Fast Track option are required to apply for admission to the MSDS.

Listed below are graduate courses in the MSDS program which students enrolled in the Fast Track option may take during their senior year. Listed next to each is the undergraduate course for which it substitutes

Students in this Fast Track option may apply no more than three of these courses toward their undergraduate Bachelor of Science major in Computer Science:

CPSC 51000 Introduction to Data Mining and Analytics substitutes for CPSC 47200 Introduction to Data Mining

CPSC 51100 Statistical Programming substitutes for either CPSC 23500 Programming for Data Analysis or CPSC 31500 Scientific Computing

CPSC 52500 Encryption and Authentication Systems substitutes for CPSC 42500 Encryption

CPSC 54000 Large-Scale Data Storage Systems substitutes for CPSC 35500 Cloud Computing and Virtualization

CPSC 55000 Machine Learning substitutes for CPSC 47100 Machine Learning

MATH 51000 Mathematics for Data Scientists substitutes for MATH 42500 Mathematical Modeling

MATH 51100 Concepts of Statistics 1 substitutes for MATH 31400 Applied Probability and Statistics or MATH 31500 Probability and Statistics 1

Degree Requirements

Program: BS-CPSC-A

I. Core Courses (35)

MATH-24000Applied Calculus

4

MATH-30700Applied Linear Algebra

3

MATH-31000Discrete Mathematics

4

CPSC-20000Introduction to Computer Science

3

CPSC-21000Programming Fundamentals

3

CPSC-24500Object-Oriented Programming

3

CPSC-30000Computer Organization

3

CPSC-34000Algorithms and Data Structures

3

CPSC-35000Operating Systems

3

CPSC-46000Programming Languages

3

CPSC-48000Communications and Networking

3

II. Capstone Sequence (6)

Complete either course sequence:
CPSC-44000Software Engineering

3

-
AND

CPSC-49200Software Systems Capstone Project

3

-
OR

CPSC-48500Advanced Communications and Networking

3

-
AND

CPSC-49300Computer Infrastructure Capstone Project

3

III. Data Science Options (9)

To earn 9 credits toward the MSDS, choose three of the following graduate courses:

CPSC 51000 Introduction to Data Mining and Analytics (3) OR CPSC 47200 Introduction to Data Mining (3)

CPSC 51100 Statistical Programming (3) OR CPSC 23500 Programming for Data Analysis OR CPSC 31500 Scientific Computing (3)

CPSC 52500 Encryption and Authentication Systems (3) OR CPSC 42500 Encryption (3)

CPSC 54000 Large-Scale Data Storage Systems (3) OR CPSC 35500 Cloud Computing and Virtualization (3)

CPSC 55000 Machine Learning (3) OR CPSC 47100 Machine Learning (3)

MATH 51000 Mathematics for Data Scientists (3) OR MATH 42500 Mathematical Modeling (3)

MATH 51100 Concepts of Statistics 1 (3) OR MATH 31400 Applied Probability and Statistics OR MATH 31500 Probability and Statistics 1 (3)

IV. Electives (3)

Choose any computer science course at or above the 200 level.

One of the following courses may substitute for the computer science elective:

MATH-30600Advanced Linear Algebra

3

MATH-31400Applied Probability and Statistics

3

MATH-31500Probability and Statistics 1

3

MATH-31600Probability and Statistics 2

3

MATH-35000Numerical Analysis

3

MATH-42500Mathematical Modeling

3

V. Advanced Writing Requirement (6)

The advanced writing requirement of the General Education curriculum is satisfied by successful completion of:
CPSC-44000Software Engineering

3

CPSC-49200Software Systems Capstone Project

3

-
OR

CPSC-48500Advanced Communications and Networking

3

CPSC-49300Computer Infrastructure Capstone Project

3