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2023-2024 University Catalog
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major: Computing & Information Sciences

Degree: Bachelor of Science (BS) Concentration: Data Science 2023-2024

Osprey Map (Course Sequence Guide)

Informational Text

The Bachelor of Science in Computing & Information Sciences requires 120 total credits.

School of Computing Policies

  • All courses must be completed with a grade of C or better unless noted otherwise.
  • Once enrolled at UNF, all remaining prerequisite courses and major/minor requirements must be completed at UNF.
  • Satisfactory Progress Policy
    • The School of Computing enforces the "one repeat" rule for all prerequisite and core courses offered by the School for its major programs.
    • Students who do not successfully complete a prerequisite, core, or major requirement for a School of Computing major on the first attempt due to earning a grade of D, F, W, WP, or WF will be granted one chance to repeat the course.
    • Students who do not successfully complete the aforementioned course on the second attempt will be blocked from registering for courses offered by the School of Computing in future semesters.
    • This policy applies whether or not the student has declared a major in a School of Computing program.
    • Students who do not obtain a B or better grade on both COP 3503 Programming II and STA 3032 Probability and Statistics for Engineers will be eligible for suspension from the program.
  • Exit Requirements
    • Proficiency in a high-level programming language.
    • Proficiency in oral communication. To demonstrate satisfactory oral communication skills, students must deliver up to two presentations in an upper-level course offered by the School of Computing. If the first presentation is satisfactory, the second presentation will be waived.

Prerequisites (11 credits)

Data Science Prerequisites (3 Courses - 11 Credits)
Additionally, the CIS major with Data Science concentration requires selective admission.

Students must meet the following admission criteria with a minimum grade of C prior to officially being admitted to the major: COP2220 Programming 1 and MAC2311 Calculus 1

COP2220 Programming I (3 Credits)
MAC2311 (GM) Calculus I (4 Credits)
MAC2312 (GM) Calculus II (4 Credits)

Requisites (14 credits)

Data Science Requisites: (4 Courses - 14 Credits)

ENC2210 (GW) Technical Writing (3 Credits)

SELECT Any public speaking course
SPC4064 Public Speaking for Professionals is recommended.

SCIENCE: Select one of the following three two-semester sequences:
BSC1010 General Biology I (4 Credits)
BSC1011 General Biology II (4 Credits)
CHM2045 General Chemistry I (3 Credits)
CHM2045L General Chemistry I Lab (1 credit) must be taken
CHM2046 General Chemistry II (3 Credits)
CHM2046L General Chemistry II Lab (1 credit) must be taken
PHY2048 (GM) Calculus-based Physics I (4 credits)
PHY2048 Calculus Physics I Lab (1 credit) must be taken
PHY2048C satisfies both the lecture and lab requirement
PHY2049 (GM) Calculus-based Physics II (4 credits)
PHY2049 Calculus Physics II Lab (1 credit) must be taken
PHY2049C satisfies both the lecture and lab requirement

Core Requirements (18 credits)

Computing Common Core (6 Courses - 18 Credits)

COP3503 Programming II (3 Credits)
COP3530 Data Structures (3 Credits)
CIS3253 GW-Legal Ethical Iss in Comput (3 Credits)
COP3703 Introduction to Databases (3 Credits)
CNT4504 Computer Networks (3 Credits)

SELECT one from the following two courses:
COT3100 Computational Structures (3 Credits)
MAD3107 Discrete Mathematics (3 Credits)

Major Requirements (32 credits)

Data Science Major Requirements: (10 Courses - 32 Credits)

MAS3105 (GM) Linear Algebra (4 Credits)
STA3163 (GM)Statistical Methods I (4 Credits)
STA3164 (GM)Statistical Methods II (3 Credits)
STA3032 (GM) Probability and Statistics for Engineers (3 Credits)
CAP3784 Introduction to Data Analytics (3 Credits)
CAP4770 Data Mining (3 Credits)
CAI4105 Machine Learning (3 Credits)
COT4400 Algorithms (3 Credits)
CAP4922 Data Science Capstone (3 Credits)

SELECT one of the following two courses:
STA4502 (GM) Non-parametric Methods in Statistics (3 credits)
STA4504 (GM) Categorical Data Analysis (3 credits)

Major Electives (9 credits)

Data Science Major Electives: (3 Courses - 9 Credits)

SELECT 9 Credits of the following:

  • COT4560 Applied Graph Theory (3 credits) 
  • COT4111 Computational Structures II (3 credits) 
  • COT4461 Computational Biology (3 credits)
  • MAD4301 Graph Theory (3 credits) 
  • MAD4203 Combinatorics (3 credits) 
  • MAD4505 Discrete Biomathematics (3 credits) 
  • MAP4231 Operations Research (3 credits) 
  • MAT4931 Special Topics in Mathematical Science (3 credits) 
  • Any upper-level Computing course not used to fulfill other requirements (prefix CAP, CDA, CEN, CIS, CNT, COP, or COT)
  • Any 4000-level Statistics course not used to fulfill other major requirements (prefix STA).
  • A maximum of 6 credit hours of CIS4900 Directed Independent Study, MAT4906 Directed Individual Studies or STA4906 Directed Individual Studies may be taken. No more than 3 credit hours CIS 4900/MAT4906/STA4906 may be taken with the same professor.
  • Students admitted to the accelerated BS-MS program may take the graduate-level courses CIS6913 Research Methods in Computing (3 Credits) and CIS6372 Information Assurance (3 Credits) to satisfy up to 6 credits of the required 9 major elective credits.

Exit Requirement

Computer and Information Sciences Oral Exit Requirement: All computing majors must deliver up to two spoken presentations in upper-level computing courses for the evaluation of presentation skills. If the first presentation is satisfactory, then the second evaluated presentation will be waived.

Electives (120 credits)

In order to graduate with a bachelor's degree, 120 total credit hours must be earned.

ANY-LEVEL Free Electives For 120 Hours

Electives (48 credits)

In order to graduate with a bachelor's degree, 48 upper-level hours must be earned.

UPPERLEVEL Free Electives From UpperLevel