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: 70-200, 70-210, 70-245, 13-240, 13-307, and 13-310; 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:

70-510 Introduction to Data Mining and Analytics substitutes for 70-472 Introduction to Data Mining

70-511 Statistical Programming substitutes for either 70-235 Programming for Data Analysis or 70-315 Scientific Computing

70-525 Encryption and Authentication Systems substitutes for 70-425 Encryption

70-540 Large-Scale Data Storage Systems substitutes for 70-355 Cloud Computing and Virtualization

70-550 Machine Learning substitutes for 70-471 Machine Learning

13-510 Mathematics for Data Scientists substitutes for 13-425 Mathematical Modeling

13-511 Concepts of Statistics I substitutes for 13-314 Applied Probability and Statistics or 13-315 Probability and Statistics I

Degree Requirements

I. Core Courses (35)

13-240	Applied Calculus	4
13-307	Applied Linear Algebra	3
13-310	Discrete Mathematics	4
70-200	Introduction to Computer Science	3
70-210	Programming Fundamentals	3
70-245	Object-Oriented Programming	3
70-300	Computer Organization	3
70-340	Algorithms and Data Structures	3
70-350	Operating Systems	3
70-460	Programming Languages	3
70-480	Communications and Networking	3

II. Capstone Sequence (6)

Complete either course sequence:

70-440	Software Engineering	3
-	AND
70-492	Software Systems Capstone Project	3
-	OR
70-485	Advanced Communications and Networking	3
-	AND
70-493	Computer Infrastructure Capstone Project	3

III. Data Science Options (9)

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

70-510 Introduction to Data Mining and Analytics (3) OR 70-472 Introduction to Data Mining (3)

70-511 Statistical Programming (3) OR 70-235 Programming for Data Analysis OR 70-315 Scientific Computing (3)

70-525 Encryption and Authentication Systems (3) OR 70-425 Encryption (3)

70-540 Large-Scale Data Storage Systems (3) OR 70-355 Cloud Computing and Virtualization (3)

70-550 Machine Learning (3) OR 70-471 Machine Learning (3)

13-510 Mathematics for Data Scientists (3) OR 13-425 Mathematical Modeling (3)

13-511 Concepts of Statistics I (3) OR 13-314 Applied Probability and Statistics OR 13-315 Probability and Statistics I(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:

13-306	Advanced Linear Algebra	3
13-314	Applied Probability and Statistics	3
13-315	Probability and Statistics I	3
13-316	Probability and Statistics II	3
13-350	Numerical Analysis	3
13-425	Mathematical Modeling	3

V. The Advanced Writing requirement for Computer Science majors pursuing the MSDS is satisfied by completing both 70-440 Software Engineering and 70-492 Software Systems Senior Project OR both 70-485 Advanced Communications and Networking and 70-493 Computer Infrastructure Senior Project.