Interdisciplinary Programs


Florida Atlantic University’s interdisciplinary programs capitalize on the advancements and knowledge of various academic disciplines to offer students unique programs of study. By combining related and sometimes unrelated disciplines across FAU colleges, these programs prepare students for multifaceted careers.

The programs listed below are offered across multiple colleges. The University also offers interdisciplinary programs shared by various departments within a college. Those programs are listed within the specific college sections.

Undergraduate Programs

Undergraduate Minor

Undergraduate Certificates

Graduate Programs

Graduate Certificates

Undergraduate Programs

Professional Studies
Bachelor of Professional Studies (B.P.S.)

(Minimum of 120 credits required) 

The Bachelor of Professional Studies (B.P.S.) is a cross-disciplinary degree program designed for working adults who have earned an A.A. or A.S. or have completed the State of Florida general education requirements but did not complete their bachelor’s degree. This degree is for individuals who have been out of college more than one year  and for whom completing a degree could lead to advancement or change in their career. The B.P.S. requires a minimum of 120 credits and completion of advanced coursework in six professional competency areas, which includes a required capstone project (IDS 4894). 

Students pursuing a Bachelor of Professional Studies will have the flexibility to take courses across colleges at FAU and in various formats, including in-person day or evening courses or online courses. Professional Studies also offers a fully online program; however, it's important to note that due to the variety of course options available under this program, a specific course may not be available in this format. To verify if a particular course is available in a fully online format, please refer to the course schedule or reach out to professionalstudies@bydsatelier.com via email. Professional Studies students are not permitted to concurrently earn a B.A. or B.S. degree. Students must meet all University and state bachelor's degree requirements.

Admission Requirements*

  1. Completion of an A.A., A.S. or the State of Florida general education requirements.
  2.  Program entry is for returning students who have not maintained continuous enrollment, as defined by University policy, at a state college and/or university.
  3.  Minimum 2.0 overall GPA.
  4.  Foreign Language Entrance Requirement: Two years of same foreign language in high school.**

* Exceptions will be considered by petition on a case-by-case basis.
** If Foreign Language Entrance Requirement was not achieved in high school, students must complete the Foreign Language Graduation Requirement: Second semester proficiency at the college level.

Degree Requirements

  1. A minimum of 120 credits overall.
  2. A minimum of a 2.0 FAU GPA.
  3. A minimum of 30 upper-division credits must be earned at FAU.
  4. A minimum of 45 upper-division credits must be 3000-4000 level or higher.
  5. Foreign Language Entrance Requirement.
  6. Civic Literacy Requirement: Only required if the student is entering the Florida College/University Public System on or after fall 2018.
  7. Summer Credit Requirement: Only required if the student is admitted to FAU with fewer than 60 transfer credits.
  8. Gordon Rule Writing and Computational Skill Requirement. Student must earn a "C" or better in each course applied to this requirement.
  9. General Education Requirement: FAU's General Education Program or A.A. degree from Florida public institution.
  10. Core competencies of 18 credits. IDS 4894 required. Student must earn a "C" or better.

Core Competencies 
18 credits with a minimum of one course from each of the six areas.  IDS 4894 required.
Advanced Writing - 3 credits
Professional Writing ENC 3213 3
Advanced Exposition ENC 3310 3
Writing for Nonprofits ENC 4354 3
Studies in Writing and Rhetoric ENG 4020 3
Rhetoric of Argument SPC 4517 3
Professional Communication and Technology - 3 credits
Organizational Communication COM 3120 3
Human Communication Theory COM 3405 3
Introduction to Business Communication: Critical Analysis and Application (effective spring 2025) GEB 3213 3
Health Delivery Systems HSA 3111 3
Contemporary Issues of Digital Data Management ISM 4041 3
Healthcare Information Systems ISM 4381 3
Principles of Advertising MAR 3326 3
Communication Skills for Public Managers PAD 3438 3
Data Management and Analysis with Excel QMB 3302 3
Small Group Processes SPC 3425 3
Intercultural Communication SPC 3710 3
Cultural Studies - 3 credits
Gender and Culture ANT 4302 3
Ethics and the Justice System CCJ 4054 3
Psychology of Human Development DEP 3053 3
Culture and Environment: Latin America and the Caribbean GEA 4405 3
Human Resource Management for Hospitality Industry HFT 3221 3
Ethics and Power in Leadership LDR 4204 3
Black Literature LIT 4355 3
Women and Literature LIT 4383 3
Literature and Environment LIT 4434 3
LGBTQ+ Literature LIT 4523 3
Human Resource Management MAN 4301 3
Diversity and Social Vulnerability in Public Safety Administration PAD 4894 3
Psychology of Women SOP 3742 3
American Multicultural Discourse SPC 3704 3
Gender, Race and Communication SPC 4712 3
Environmental Sociology SYD 3510 3
Poverty and Society SYO 3534 3
Leadership and Management - 3 credits
Entrepreneurship ENT 4024 3
Introduction to Hospitality Management HFT 3003 3
Meetings and Event Management HFT 3741 3
Hospitality Marketing and Revenue Management HFT 4503 3
Introduction to Health Professions HSA 3104 3
Management of Long-Term Care Facilities HSA 4223 3
Leadership and Social Change LDR 3216 3
Theories of Leadership LDR 4104 3
Introduction to Field Leadership LDR 4250 3
Introduction to Management and Organizational Behavior MAN 3025 3
Service Operations MAN 4029 3
Managing for Excellence in Public and Nonprofit Sectors PAD 4332 3
Global Studies - 3 credits
Cultures of South Asia ANT 3361 3
Global Environmental Politics and Policies INR 4350 3
Contemporary Issues in Leadership LDR 3115 3
World Literature: Critical Approaches LIT 4225 3
Major Writers of World Literature in English LIT 4244 3
International Business Negotiations MAN 3442 3
International Business MAN 3600 3
Globalization and Social Movements SYP 3454 3
Global Social Change SYP 4453 3
Study Abroad (must be upper division and an approved course) 3
Career Enrichment Requirement - 3 credits
Professional Internship IDS 3949 0-4
RI: Professional Capstone (Req uired) IDS 4894 1-4
Capstone Seminar on Leadership LDR 4951 3
Professional Development SLS 4342 3
Directed Independent Study Any prefix with 4905/4906 1-4 
Electives (if needed)
If elective coursework is needed to complete the total of 120 credits or the upper-division or residency minimums, please see the program academic advisor for a list of suggested courses.


Returning students are highly encouraged to take SLS 3115, Foundations for Personal Academic and Professional Development in the first semester.

Students are strongly encouraged to gain practical experience through participation in internship opportunities. For more information, contact the FAU Career Center at 561-297-3533 or visit the website.

Honors Program in Professional Studies

The Honors in Professional Studies Program provides FAU’s students in the Bachelor of Professional Studies (B.P.S.) program the opportunity to achieve academic excellence beyond the level of standard coursework. Students interested in pursuing the Honors designation in the Professional Studies Program need to meet the following eligibility and admission requirements.

Requirements for Eligibility and Admission to the Honors in Professional Studies Program
The number of students in the program is limited to 20 percent of students within the Bachelor of Professional Studies Program. To be eligible for the program, students must:

  1. Meet all university requirements to declare major in the B.P.S. program;
  2. Complete the equivalent of a full-time enrollment semester at FAU (12 credits) with a cumulative GPA of at least 3.25; and
  3. Submit a formal application after completion of, or in the semester when, 12 credits are completed and prior to the beginning of the semester in which student seeks to enroll in the Honors in Professional Studies Program

The application package should include:

  1. Application Form;
  2. Unofficial transcript;
  3. Personal statement;
  4. A letter of support from a member of the Professional Studies Faculty (This should be from one
    of the faculty members from one of the 12 credits of courses already taken in requirement 2); and
  5. Interview with Program’s Coordinator and Advisor.


Requirements to Maintain Eligibility in the Honors Professional Studies Program

  1. Maintain good academic and ethical standing;
  2. Maintain cumulative GPA of 3.25 in the 12 credits of Honors-in-the-Major coursework; and
  3. Maintain cumulative GPA of at least 3.25 in the final 30 credits, which includes the Honors
    coursework.

If any of the above standards for maintaining eligibility in the program are not met, students will be advised accordingly on how to undertake remedial actions after meeting with the Program’s Coordinator and Advisor.

Students will not be allowed to continue in the Honors in Professional Studies Program for:

  1. Any violation of the Code of Academic Integrity; or
  2. Any grade of less than a “B” in an Honors-in-the-Major course requirement.


Program Enrichment Requirements
Honors-level enrichment seeks to enhance students' experience in the program. For students to receive the Honors-in-the-Major designation, the following enrichment requirements must be met:

General Enrichment Requirement
Students in the Honors in Professional Studies Program will be required to complete one of the
following:

  1. Join a professional or honors organization;
  2. Participate in extensive mentoring in practical research or internship by a faculty member (e.g., a Summer Undergraduate Research Fellowship (SURF), an Undergraduate Research Grant);
  3. Submit research to any of the FAU Research Symposia;
  4. Submit research to FAU’s Undergraduate Research Journal or appropriate external publication (to be approved by the Program’s Coordinator and Advisor);
  5. Once per semester, attend a faculty seminar or professional development seminar (to be approved by the Program’s Coordinator and Advisor); and

Other enrichment activity as approved by the Program’s Coordinator and Advisor.

Coursework Requirement
The Honors in Professional Studies Program requires completion of 9 credits of coursework. These 9 credits can be any combination of Honors-Level designated courses or courses where additional enrichment requirements have been agreed upon between the student and the instructor of the course as per the guidelines of the Honors Compact contract.

Honors Compact Procedure
Students must register for an approved upper-division course that may be designated as Honors-level with an Honors Compact. These are to be determined in consultation with the Program’s Coordinator and Advisor.

  1. The student approaches the instructor and requests the course be designated as Honors;
  2. The decision is entirely the instructor’s; however, the Program’s Coordinator and Advisor will work closely with instructors to facilitate the process.
  3. Once the instructor and the student agree on the terms of the Honors Compact (ideally before the drop/add date), the signed document is forwarded to the University Honors Program Director for final approval.

Ideally, Honors courses (Honors Compacts) should be completed no later than the equivalent of the next
to last semester at FAU.

Honors Capstone Project Requirement
Student will complete IDS 4894 RI: Professional Capstone (as an Honors Compact) for 3 credits. The final
honors capstone product or performance is assessed by the faculty supervisor and involves a public capstone presentation or performance.

Data Science and Analytics
Bachelor of Science (B.S.)

Data Science in the Natural Sciences Concentration
Data Science and Engineering Concentration
Data Science in Business Concentration

(Minimum of 120 credits required)

The Bachelor of Science with Major in Data Science and Analytics (BSDSA) is a multi-college, interdisciplinary program jointly administered by the Department of Mathematics and Statistics in the Charles E. Schmidt College of Science, the Department of Electrical Engineering and Computer Science (EECS) in the College of Engineering and Computer Science, the Department of Information Technology and Operations Management (ITOM) in the College of Business, the Department of Political Science in the Dorothy F. Schmidt College of Arts and Letters and the School of Criminology and Criminal Justice in the College of Social Work and Criminal Justice. The program aims to prepare students with the essential skill sets across disciplines needed for data-driven applications in industry, business and government. To allow for maximum flexibility in career aspirations, students can select from three concentrations:

Admission Requirements
All students must meet the minimum admission requirements of the University. Refer to the Admissions section of this catalog.

Prerequisite Coursework for Transfer Students
Students transferring to Florida Atlantic University must complete lower-division requirements including the requirements of the General Education Program, College Algebra and Introductory Statistics. Lower-division requirements may be completed through the A.A. degree from any Florida public college, university or community college, or through equivalent coursework at another regionally accredited institution. Before transferring and to ensure timely progress toward the BSDSA degree, students must also complete the prerequisite courses for their major as outlined in the Transition Guides. 

All courses not approved by the Florida Statewide Course Numbering System that will be used to satisfy requirements will be evaluated individually on the basis of content and will require a catalog course description and a copy of the syllabus for assessment.

Capstone
The Capstone for the B.S. degree with major in Data Science and Analytics is a cross college course that can be taken multiple times with a minimum of 3 credits as a requirement for the degree. Students apply their theoretical knowledge, methods and tools acquired during the Data Science and Analytics program to a real-world problem and engage in processing data and applying appropriate analytic methods to the problem. Students implement a solution using appropriate tools and can work individually or in teams under the supervision of the course instructor or another faculty member. This can be accomplished in three ways: an approved Project, Research Experience or Written Thesis.

Degree Requirements
The minimum number of credits required for the Bachelor of Science with major in Data Science and Analytics is 120 credits: 36 credits in the General Education Program, 48 credits of major requirements and up to 36 credits of general e lectives. Additional requirements:

  1. A minimum of 45 upper-division credits;
  2.  Students must attain a minimum grade of "C" in all major courses to receive credit in the major; and
  3.  No major course with a pass/fail grade will be accepted.

The 48 required credits for the major are listed below.

Common Core
Tools for Data Science CAP 2751 3
Experimental Design and Data Analysis CAP 2753 3
Artificial Intelligence for Social Good CCJ 3071 3
Data Science Capstone ISC 4941 3
Mathematics for Data Science MAP 2192 3
Data Management and Analysis with Excel QMB 3302 3
Introductory Statistics STA 2023 3
Common Core Credits 21
Electives
Choose two courses from the List of Elective Courses for all Concentrations
Elective Credits 6


Data Science in the Natural Sciences Concentration

Concentration Core Requirements
RI: Introduction to Data Science CAP 3786 3
Introduction to Computational Mathematics MAD 2502 3
Computational Statistics STA 3100 3
Concentration Core Credits 9
Concentration Core Electives. Choose four courses.
Cryptography and Information Security CIS 4362 3
Graph Theory MAD 4301 3
Applied Mathematical Modeling MAP 4103 3
RI: Industrial Problems in Applied Math MAP 4913 3
Topology for Data Science MTG 4325 3
SAS for Data and Statistical Analyses STA 3024 3
Introduction to Biostatistics STA 3173 3
Applied Statistics 1 Lab STA 4202L 1
Statistical Designs STA 4222 3
Applied Statistics 1 STA 4234 2
Probability and Statistics 1 STA 4442 3
Probability and Statistics 2 STA 4443 3
Applied Statistics 2 STA 4702 3
Applied Time Series and Forecasting STA 4853 3
Concentration Elective Credits 12
Concentration Credits 21


Data Science and Engineering Concentration 

Concentration Core Requirements 
Introduction to Data Science and Analytics CAP 4773 3
Introduction to Software Design CEN 3062C 3
Introduction to Programming in Python COP 3035C 3
Data Structures and Algorithm Analysis with Python COP 3410C 3
Concentration Core Credits 12 
Concentration Core Electives. Choose three courses or four courses so that the total of concentration credits is 21.
Introduction to Deep Learning CAP 4613 3
Introduction to Artificial Intelligence CAP 4630 3
Introduction to Data Mining and Machine Learning CAP 4770 3
Introduction to Computer Systems Performance Evaluation CEN 4400 3
Introduction to Database Structures COP 3540 3
Introduction to Web Programming COP 3834 3
Python Programming COP 4045 3
Applied Database Systems COP 4703 3
Concentration Elective Credits 9
Concentration Credits 21


* Students who have taken a college-level introductory course in programming may substitute this course with one of the Concentration Elective Courses, with permission of the advisor.

 Data Science in Business Concentration

Concentration Core Requirements
Business Communication for Data Analysts GEB 3231 3
Introduction to Business Analytics and Big Data ISM 3116 3
Data Mining and Predictive Analytics ISM 4117 3
Advanced Business Analytics ISM 4403 3
Concentration Core Credits 12
Concentration Core Electives. Choose three courses.
Revenue Management and Predictive Analytics in the Hospitality and Tourism Industry HFT 4481 3
Contemporary Issues of Digital Data Management ISM 4041 3
Database Management Systems ISM 4212 3
Management of Information Assurance and Security ISM 4323 3
Social Media and Web Analytics ISM 4420 3
Business Analytics for Marketing and Customer Relationship Management MAR 4615 3
Concentration Elective Credits 9
Concentration Credits 21


Electives Table

Arts and Letters Electives
Research Methods in Bioarchaeology ANT 4192 3
Information Technology in Public Administration PAD 3712 3
Introduction to the Nonprofit Sector PAD 4144 3
Quantitative Inquiry for Public Managers PAD 4702 3
Research Methods for Public Management PAD 4704 3
RI: Research Methods in Political Science POS 3703 3
Public Opinion and American Politics POS 4204 3
Sociological Analysis: Quantitative Methods SYA 4400 3
Business Electives
Business Communication for Data Analysts GEB 3231 3
Revenue Management and Predictive Analytics in the Hospitality and Tourism Industry HFT 4481 3
Introduction to Business Analytics and Big Data ISM 3116 3
Contemporary Issues of Digital Data Management ISM 4041 3
Data Mining and Predictive Analytics ISM 4117 3
Database Management Systems ISM 4212 3
Management of Information Assurance and Security ISM 4323 3
Advanced Business Analytics ISM 4403 3
Social Media and Web Analytics ISM 4420 3
Business Analytics for Marketing and Customer Relationship Management MAR 4615 3
Engineering Electives
Introduction to Deep Learning CAP 4613 3
Introduction to Artificial Intelligence CAP 4630 3
Introduction to Data Mining and Machine Learning CAP 4770 3
Introduction to Data Science and Analytics CAP 4773 3
Introduction to Computer Systems Performance Evaluation CEN 4400 3
Introduction to Database Structures COP 3540 3
Introduction to Internet Computing COP 3813 3
Python Programming COP 4045 3
Applied Database Systems COP 4703 3
Science Electives
Solar System Astronomy AST 3110 3
Laboratory Methods in Biotechnology BSC 4403L 3
Concepts in Bioinformatics BSC 4434C 3
RI: Introduction to Data Science CAP 3786 3
Cryptography and Information Security CIS 4362 3
Spatial Data Analysis GEO 4167C 3
Photogrammetry and Aerial Photograph Interpretation GIS 4021C 3
Applications of Geographic Information Systems GIS 4048C 3
Geospatial Databases GIS 4118 3
Graph Theory MAD 4301 3
Applied Mathematical Modeling MAP 4103 3
RI: Industrial Problems in Applied Math MAP 4913 3
Epidemiology of Infectious Diseases MCB 4276 3
Topology for Data Science MTG 4325 3
Practical Cell Neuroscience PCB 4843C 3
Computational Physics PHZ 3151C 3
Mathematical Methods for Physics PHZ 4113 3
SAS for Data and Statistical Analyses STA 3024 3
Computational Statistics STA 3100 3
Introduction to Biostatistics STA 3173 3
Applied Statistics 1 Lab STA 4202L 1
Statistical Designs STA 4222 3
Applied Statistics 1 STA 4234 2
Probability and Statistics 1 STA 4442 3
Probability and Statistics 2 STA 4443 3
Applied Statistics 2 STA 4702 3
Applied Time Series and Forecasting STA 4853 3
Social Work and Criminal Justice Electives
Teen Technology Misuse CCJ 4554 3
Methods of Research in Criminal Justice CCJ 4700 3
Criminal Justice Technology CJE 3692C 3
Crime Analysis CJE 4663 3
Computer Crime CJE 4668 3
Research Methods in Social Work SOW 4403 3

 

Health Humanities
Undergraduate Minor

(Minimum of 15 credits)

The minor in Health Humanities is open to all undergraduate students at FAU. The minor is awarded upon graduation from an undergraduate program at FAU; it is not awarded independently of an undergraduate degree.

Requirements
Requirements for the minor include completion of 15 credits with a minimum overall GPA of 2.0. Students must complete at least 12 credits in the Dorothy F. Schmidt College of Arts and Letters, with at least 9 credits at the upper-division (3000-4000) level.

The courses listed below are all electives and are pre-approved for the minor. Courses from outside the College of  Arts and Letters are listed so that students in those colleges may know which courses from their own college may be applied to the Health Humanities minor. For consideration of courses not listed below, please contact the minor program director, Prof. Michael Rapoport. 

Dorothy F. Schmidt College of Arts and Letters    
Anthropology    
Introduction to Biological Anthropology ANT 2511 3
The Anthropology of Death ANT 4025 3
Environment and Disease ANT 4463 3
Culture, Gender and Health ANT 4469 3
Global Health and Culture ANT 4489 3
Biological Anthropology ANT 4514 3
Epidemics: Culture, Science and Policy ANT 4532 3
English    
Victorian Genres and Themes (when related to health) ENL 4264 3
Special Topics (when related to Illness, Madness and Visions) LIT 2931 3
Literature and Environment LIT 4434 3
History    
History of U.S. Drug and Alcohol Use AMH 4315 3
Languages, Linguistics and Comparative Literature    
Spanish for Careers  SPN 2161 3
Spanish for Healthcare Professionals SPN 2162 3
Intermediate Spanish Conversation SPN 2240 3
Music    
Alexander Technique for the Musician MUS 4802 3
Introduction to Vocal Pedagogy MVV 2601 3
Vocal Pedagogy MVV 4640 3
Philosophy    
Philosophy of Psychiatry PHI 3453 3
Philosophy of Medicine PHI 3456 3
Philosophy of Science PHI 4400 3
Biomedical Ethics PHI 4635 3
Sociology    
Special Topics (when related to Care and Care Work) SYA 3930 3
Sociology of the Body SYD 3804 3
Sociology of Health, Medicine and Illness SYO 3400 3
Sociology of Mental Health SYO 3410 3
Drugs and Society SYP 3550 3
Sociology of Aging and Dying SYP 3740 3
College of Business    
Health Administration    
Introduction to Health Professions HSA 3104 3
Health Delivery Systems HSA 3111 3
Health Care Medical Terminology HSA 3534 3
Issues and Trends in Health Care HSA 4113 3
International Healthcare Systems HSA 4124 3
Management of Long-Term Care Faclities HSA 4223 3
Health Law HSA 4423 3
Christine E. Lynn College of Nursing    
Foundations of Caring in Nursing Situations (Nursing students only) NUR 3115 3
Charles E. Schmidt College of Science    
Biological Sciences    
Molecular Genetics of Aging BSC 4022 3
Climate Change Biology: Ecosystems to Human Health BSC 4307 3
Concepts in Bioinformatics BSC 4434C 3
Biology of Cancer BSC 4806 3
Microbiology for Health Services MCB 2004 3
Medical Bacterioogy MCB 4203 3
Epidemiology of Infectious Diseases MCB 4276 3
Cell Biology PCB 3023 3
Genetics PCB 3063 4
Evolution PCB 3674 3
Principles of Human Neuroanatomy ZOO 4742 3
Chemistry and Biochemistry    
RI: Introduction to Drug Design CHM 4273 3
Introduction to Drug Development CHM 4274C 3
Introduction to Drug Formulation CHM 4276C 3
Medicinal Chemistry CHM 4292 3
Exercise Science and Health Promotion    
Perspectives in Health HSC 3102 3
Stress Management HSC 4104 3
Substance Abuse HSC 4143 3
Health Promotion HSC 4581 3
Obesity: Biological, Psychological and Cultural Factors PET 4263 3
Interdisciplinary Studies    
Health Science 1 IDS 2122 3
Introduction to Preprrofessional Studies PCB 3083 3
Psychology    
Psychopathology CLP 4144 3
Clinical Psychology CLP 4343 3
Psychology of Human Development DEP 3051 3
Psychology of Women SOP 3742 3

 

Cybersecurity
Undergraduate Minor
Undergraduate Certificate

(Minimum of 12 credits required) 

Cybersecurity is the study of methods to ensure information and system security. Industry and government need an educated workforce to serve as information and systems security analysts, security and network administrators and more. Due their extensive expertise and facilities, the departments of Information Technology and Operations Management (in the College of Business), Electrical Engineering and Computer Science (In the College of Engineering and Computer Science) and Mathematics and Statistics (in the College of Science) have jointly designed the Cybersecurity Minor and Certificate. Three tracks, each requiring 12 credits, constitute the minor and certificate: Information Technology (IT), Computer Science (CS) and Mathematical Sciences (MS).

Tracks
IT Cybersecurity Track: The 12 credits should be completed as follows: one IT core course, two 3-credit courses from the IT elective list and one 3-credit course from the IT, CS or MS elective course lists. A maximum of 3 credits used for the minor may count toward other major requirements. A minimum of two courses (6 credits) must be exclusive to the minor.

CS Cybersecurity Track: The 12 credits should be completed as follows: one CS core course, two 3-credit courses from the CS elective course list and one 3-credit course from the IT, CS or MS elective course lists.

MS Cybersecurity Track: The 12 credits should be completed as follows: one MS core course, two 3-credit courses from the MS course list and one 3-credit course from the IT, CS or MS elective course lists.

Admission
Open to students who satisfy the prerequisites required for each course in the program with a minimum grade of "C." Each track in the program requires 12 credits with minimum grades of "C" in all courses. Students cannot obtain both a certificate and a minor. All course materials are in English. All international students must demonstrate proficiency in English to enter the program.

The certificate is available to degree-seeking students, non-degree students and working professionals. Students pursuing the certificate may apply for it in the college where the track is located upon successful completion of the coursework.

IT Cybersecurity Track
Required IT Core Course
Business Data Communications ISM 4220 3
IT elective courses: Select two from this list and one more from any track list
Introduction to Cybersecurity ISM 4320 3
Management of Information Assurance and Security ISM 4323 3
Computer Forensics ISM 4324 3

 

CS Cybersecurity Track
Required CS Core Course
Foundations of Cybersecurity CNT 4403 3
CS elective courses: Select two from this list and one more from any track list. Additional courses may be used as replacements with prior approval of the department.
Trustworthy Artificial Intelligence CAP 4623 3
Introduction to Cryptographic Engineering CDA 4321 3
Cyber Physical Systems Security CIS 4213 3
Operating Systems Security CIS 4367 3
Network and Data Security CNT 4411 3

 

MS Cybersecurity Track
Required MS Core Course
Cryptography and Information Security CIS 4362 3
MS elective courses: Select two from this list and one more from any track list
RI: Introduction to Data Science CAP 3786 3
Introduction to Coding Theory MAD 4605 3
Mathematics of Cybersecurity MAP 4190 3
Mathematics for Cryptography MAS 4206 3

 

The FAU Max Planck Honors Program (MPHP)

Eligible College of Science majors in Biology, Psychology, Neuroscience and Behavior, and Medical Biology may apply to participate in this Jupiter-specific honors program for undergraduates. For students pursuing the MPHP, 3 to 6 of the elective credits in their individual program must be applied toward the requirements of the MPHP. These include successful completion of a Capstone experience (1 to 3 credits) and three different MPHP Enrichment courses (1 credit each) from those listed below. A minimum grade of "B" must be achieved in graded courses ("S" in non-graded courses) among these exclusive MPHP course options for the credits to count toward the requirements of the MPHP. Visit the MPHP website to apply.

FAU Max Planck Honors Program Required Coursework
Core Course (required for all participants)
Honors Introduction to Neuroscience Research PSB 4003 1
Enrichment Course Electives (at a minimum, two different courses are required)
Honors Scientific Communication BSC 4934 1
Honors Advanced Cell Imaging for Neuroscientists PCB 4933C 1
Honors Advanced Genetics PCB 4935 1
Honors Advanced Physiology PCB 4937C 1
Honors Advanced Scientific Grant Writing PCB 4956 1
Honors Life Science Technologies PSB 4110 1
Honors Advanced Techniques in Neuroscience PSB 4112C 1
Honors Directed Independent Research PSB 4916 0-3
Honors Symposium Presentation PSB 4922 1
Honors Special Topics in Neuroscience PSB 4931 1-3
Max Planck Honors Seminar PSB 4932 1
Honors Journal Club in Neuroscience PSB 4951 1
Capstone Options (at least 3 credits in one of the following courses is required)
FAU Max Planck Honors Capstone PSB 4902 1-3
Honors Mentored Research PSB 4910 1-3
FAU Max Planck Honors Thesis PSB 4970 1-3

 

Interdisciplinary Applications of Artificial Intelligence
Undergraduate Minor
Undergraduate Certificate

(Minimum of 12 credits required)

This minor or certificate require completion of four courses (12 credits) with a minimum grade of "C." Students must ensure that they have the necessary prerequisites for the selected courses. Waiver of prerequisites will be made on a case-by-case basis. Students cannot apply for both the minor and certificate in Interdisciplinary Applications of AI. Students can apply to one track at most.

The certificate is available to degree-seeking students, non-degree students and working professionals.

The minor is available to all undergraduate degree-seeking students and may be earned upon successful completion of the coursework below and the simultaneous completion of a bachelor's degree at FAU.
For the minor:

  1. At least 9 of the 12 credits must be earned from FAU.
  2. A t least 9 of the 12 credits must be upper-division credits.

Tracks
The program contains four tracks from different disciplines.

Societal Applications of Artificial Intelligence. This 12-credit track is offered by the Department of Philosophy in the Dorothy F. Schmidt College of Arts and Letters. The program provides students with a fundamental awareness of how Artificial Intelligence (AI) operates, an understanding of how AI is utilized and comprehension of the consequences of those applications in various societal domains. The program requires no prior formal engineering or technical expertise.

Core Courses - 6 credits
Select two courses from the following four courses. At least one of the two core courses must be AMH 3372 or PHI 2681.
History of American Technology AMH 3372 3
Applications of Artificial Intelligence CAP 2603 3
Applied Machine Learning and Data Mining CAP 4612 3
Ethics and Artificial Intelligence PHY 2681 3
Elective Courses - 6 credits
Select two courses from the Electives Table.


Business Applications of Artificial Intelligence. This 12-credit track is offered by the Department of Information Technology and Operations Management (ITOM) in the College of Business. It requires no prior, formal engineering or technical experience. The program offers a business manager’s level of understanding of Artificial Intelligence and how it can be positioned to improve efficiency and effectiveness across the organization, including what is the basket of AI tools that can be used in what business problems, how to customize available AI tools for the specific organizational problem and be successful, and how to avoid caveats.

Core Courses - 6 credits
Select two courses from the following four courses. At least one of the two core courses must be ISM 4041 or ISM 4421.
Applications of Artificial Intelligence CAP 2603 3
Applied Machine Learning and Data Mining CAP 4612 3
Contemporary Issues of Digital Management ISM 4041 3
Artificial Intelligence and Digital Transformation for Business ISM 4421 3
Elective Courses - 6 credits
Select two courses from the Electives Table.


Technology Applications of Artificial Intelligence. This 12-credit track is offered by the Department of Electrical Engineering and Computer Science in the College of Engineering and Computer Science. Artificial Intelligence is making agriculture more precise and efficient, revealing new medical technologies and bringing the prospect of autonomous transportation and advanced manufacturing closer to reality. To become competitive, companies and corporations will have to embrace AI technological innovations to some extent. This program requires no prior formal engineering or technical experience. It provides students with knowledge and skills in the concepts, technologies and applications of Artificial Intelligence.

Core Courses - 6 credits
Applications of Artificial Intelligence CAP 2603 3
Applied Machine Learning and Data Mining CAP 4612 3
Elective Courses - 6 credits
Select two courses from the Electives Table.


Scientific Applications of Artificial Intelligence. This 12-credit track is offered by the Department of Mathematics and Statistics in the Charles E. Schmidt College of Science. The program provides students, through hands-on experience, an introduction to how Artificial Intelligence impacts the analysis of scientific data to gain a better understanding of natural, physical and social phenomena.

Core Courses - 6 credits
Select two courses from the following three courses.
Applications of Artificial Intelligence CAP 2603 3
RI: Introduction to Data Science CAP 3786 3
Applied Machine Learning and Data Mining CAP 4612 3
Elective Courses - 6 credits
Select two courses from the Electives Table. At least one course must be chosen from the College of Science elective group.

 

Electives Table - 6 credits
Select two courses.
College of Arts and Letters Courses
History of American Technology AMH 3372 3
New Media and Civic Discourse COM 4603 3
Science Fiction LIT 3313 3
Psycholinguistics LIN 4701 3
Media, Culture and Technology MMC 4263 3
Information Technology in Public Administration PAD 3712 3
Artificial Intelligence and Ethics PHI 2680 3
Philosophy of Mind PHI 3320 3
RI: Research Methods in Political Science POS 3703 3
Technology and Society SYP 4421 3
College of Business Courses
Revenue Management and Predictive Analytics in the Hospitality and Tourism Industry HFT 4481 3
Technology in Health Care Organizations HSA 3191 3
Introduction to Business Analytics and Big Data ISM 3116 3
Contemporary Issues of Digital Data Management ISM 4041 3
Healthcare Information Systems ISM 4381 3
Artificial Intelligence and Digital Transformation for Business ISM 4421 3
Blockchain: Business Implications ISM 4451 3
Project Management MAN 4583 3
Business Analytics for Marketing and Customer Relationship Management MAR 4615 3
Digital Marketing MAR 4721 3
College of Engineering and Computer Science Courses
Applications of Artificial Intelligence CAP 2603 3
Tools for Data Science CAP 2751 3
Applied Machine Learning and Data Mining CAP 4612 3
Introduction to Deep Learning CAP 4613 3
Introduction to Artificial Intelligence CAP 4630 3
Trustworthy Artificial Intelligence CAP 4623 3
Introduction to Data Mining and Machine Learning CAP 4770 3
Introduction to Data Science and Analytics CAP 4773 3
Special Topics (such as: Robotic Applications) EEL 4930 3
College of Science Courses
Solar System Astronomy AST 3110 3
Laboratory Methods in Biotechnology BSC 4403L 3
Concepts in Bioinformatics BSC 4434C 3
RI: Introduction to Data Science CAP 3786 3
Spatial Data Analysis GEO 4167C 3
Photogrammetry and Aerial Photograph Interpretation GIS 4021C 3
Applications of Geographic Information Systems GIS 4048C 3
Geospatial Databases GIS 4118 3
Mathematics of Data Science MAP 2192 3
RI: Industrial Problems in Applied Math MAP 4913 3
Epidemiology of Infectious Diseases MCB 4276 3
Topology for Data Science MTG 4325 3
Practical Cell Neuroscience PCB 4843C 3
Computational Physics PHZ 3151C 3
Mathematical Methods for Physics PHZ 4113 3
Computational Statistics STA 3100 3
Introduction to Biostatistics STA 3173 3
Applied Statistics 1 STA 4234 3
RI: Shared and Automated Transport: Current Trends URP 4712 3
College of Social Work and Criminal Justice Courses
Artificial Intelligence for Social Good CCJ 3071 3
Crime Analysis CJE 4663 3
Computer Crime CJE 4668 3

 

Undergraduate Certificates

Applied Mental Health Services
Undergraduate Certificate

(Minimum of 17 credits required)

The undergraduate certificate in Applied Mental Health Services, offered jointly by the Department of Psychology and by the Department of Counselor Education in the College of Education, provides a curricular experience for students who wish to pursue careers in clinical psychology, mental health counseling and allied human services that enhances the student's chosen major. This program is also specialized training for students who wish to pursue graduate degrees in these critical-need careers.

Students who have completed 60 credits with a GPA of 3.0 or better may apply for the certificate program. The program requires a minimum of 17 credits by completing the psychology and counselor education courses below. Students must attain a 3.0 GPA or better to qualify for the certificate. A grade of "C-" or better (unless otherwise noted in the course description) is required in all psychology courses taken as part of the requirements for the Applied Mental Health Services certificate. Students receiving a bachelor's degree in the Department of Psychology will meet the requirements for certification by completing the courses listed below, as well as their prerequisites. Students from other departments should meet with an advisor to determine eligibility and requirements for this certificate program. Students who qualify will receive a certificate of completion and a notation on their transcript.

Required Courses - 15 credits
Psychopathology CLP 4144 3
Clinical Psychology CLP 4343 3
Neuropsychology PSB 4240 3
Career and Lifespan Development SDS 3340 3
Interpersonal Communication Skills SDS 4410 3

 

Elective Courses - 2 credits, minimum 
Forensic Psychology CLP 4390 3
Special Topics (in Counseling)*, ** MHS 5930 3
University Student Mentoring and Peer Coaching * SDS 3483 2
Police Psychology SOP 4750 3
Psychology and the Law SOP 4751 3


* Course offered in the Department of Counselor Education in the College of Education.
** Prerequisite: Permission of instructor.


Data Science
Undergraduate Certificate

(Minimum of 15 credits required)

Data Science is the study of methods to manage, analyze and extract knowledge from data. Industry and government need an educated workforce with the necessary expertise to make use of the enormous volumes of data available to them. Due to their extensive expertise and facilities, the departments of Mathematics and Statistics and Electrical Engineering and Computer Science have jointly designed the Data Science certificate. This 15-credit certificate program has two tracks: Mathematical Sciences (MathSci) and Computer Science and Analytics (CS). The Data Science certificate draws the 15 credits from Computer Science, Mathematics and Statistics.

Admission
The program is open to students who satisfy the prerequisite courses required for each course in the certificate curriculum. Both tracks - MathSci and CS - require two core courses and three elective courses for a total of 15 credits. All five courses must be completed with a grade of "C" or better.

Core Courses - 6 credits
RI: Introduction to Data Science CAP 3786 3 or
Introduction to Data Science and Analytics CAP 4773 3 or
Introduction to Data Science CAP 5768 3
Probability and Statistics for Engineers STA 4032 3 or
Probability and Statistics 1 STA 4442 3 or
Stochastic Models for Computer Science STA 4821 3
Elective Courses by Track - 9 credits  
MathSci Track
Select two from the following courses and one more from this list or the list of CS elective courses.
RI: Computational Statistics STA 4102 3
Statistical Designs STA 4222 3
RI: Statistical Learning* STA 4241 3
Applied Statistics 1 STA 4234 2
Applied Statistics 1 Lab STA 4202L 1
Applied Statistics 2* STA 4702 3
Applied Time Series and Forecasting STA 4853 3
* Recommended electives.
CS Track
Select two from the following courses and one more from this list or the list of MathSci elective courses.
Introduction to Deep Learning CAP 4613 3
Introduction to Artificial Intelligence CAP 4630 3
Introduction to Data Mining and Machine Intelligence CAP 4770 3
Introduction to Computer Systems Performance Evaluation CEN 4400 3
Introduction to Database Structures COP 3540 3
Applied Database Systems COP 4703 3

 

Undergraduate Research
Undergraduate Certificate

(Minimum of 12 credits required)

To recognize undergraduate students' excellence in undergraduate research, the Office of Undergraduate Research and Inquiry (OURI) has established the Undergraduate Research Certificate. Requirements for the Research Certificate include completion of 12 credits of research exposure, skill-building and intensive courses as well as dissemination of the outcomes of students' research and inquiry through a research presentation or exhibition.

Degree-seeking undergraduate students may earn the Research Certificate by completing the following requirements.

  1. 12 credits of coursework related to undergraduate research from the following:

    1. Up to 6 credits of General Education Program courses or Honors Core courses (for Wilkes Honors College students) at the Research Level including:

      Research Exposure, General Education Courses Approved List
      Honors Introduction to Anthropology ANT 2000 3
      Life Science Lab or RI: Life Science Lab BSC 1005L 1
      Contemporary Chemical Issues CHM 1020C 3
      General Chemistry For the Health Sciences CHM 2032 3
      General Chemistry 1 CHM 2045 3
      Honors Psychopathology CLP 4143 3
      Principles of Macroeconomics ECO 2013 3 or
      Principles of Microeconomics ECO 2023 3
      Disability and Society EEX 2091 3
      The Blue Planet ESC 2000 3
      Honors 20th Century Europe EUH 2341 3
      Honors Freshman Seminar in History HIS 1933 3
      Honors Ways of Knowing PHI 2361 3
      Honors Privacy POS 3623 3
      Introductory Statistics STA 2023 3
      Social Problems SYG 2010 3
    2. Up to 3 credits of Research Skill-Building coursework in research methods from the approved list below.
    3. At least 3 credits of Research-Intensive-designated courses and/or Directed Independent Research. Honors thesis and courses with honors compacts can substitute for the Research- Intensive designation.

  2. Presentation at one of the FAU Undergraduate Research Symposia (Boca Raton, Broward and Jupiter), Senior Engineering Design Showcase, Charles E. Schmidt College of Science Undergraduate Poster Competition or appropriate discipline-specific conferences, symposia, exhibitions, or showcases (internal or external), as approved by the University's Undergraduate Research Curriculum Committee. For internal symposia, students register for a zero-credit course: IDS 4914, Undergraduate Research Forum. For the Senior Engineering Design Showcase, students will receive credit for the dissemination of their research upon successful completion of one of the following courses: CGN 4804C, EGN 4952C, EOC 4804L or EML 4551 with a minimum grade of "C." (Change effective fall 2024.)

Additional stipulations include:

  1. Courses that are taken S/U may count toward the certificate with a grade of Satisfactory; for courses with standard grading, students must complete the courses with a minimum grade of "C."
  2. A maximum of 3 transfer credits may be applied to the certificate.
  3. Course substitutions will be reviewed by the Undergraduate Research Curriculum Committee on a case-by-case basis.
  4. Students should consult with the Office of Undergraduate Research and Inquiry and/or their undergraduate advisor for more information.

Research Skill-Building Approved List
A&L Archaeological Research Methods ANT 4116 3
A&L Research Methods in Bioarchaeology ANT 4192 3
A&L Research Methods in Cultural/Social Anthropology ANT 4495 3
A&L Architectural Research Methods and Analysis ARC 3091 3
A&L Architectural Theory ARC 4219 3
A&L Architectural Design 7 ARC 4327 3
A&L Architectural Design 8 ARC 4328 3
A&L Advanced Architectural Design 1 ARC 5328 3
A&L Topical Design Studio ARC 5352 3
A&L Introduction to Urban Design ARC 6305 3
A&L Conflict and Communication COM 3462 3
A&L Principles of Research Writing ENC 4138 3
A&L Research and Bibliographic Methods FOL 3880 3
A&L Program Evaluation in Public Management PAD 4320 3
A&L Quantitative Inquiry for Public Managers PAD 4702 3
A&L Research Methods for Public Management PAD 4704 3
A&L RI: Research Methods in Political Science POS 3703 3
A&L Qualitative Research Methods SYA 4310 3
A&L Sociological Analysis: Quantitative Methods SYA 4400 3
BUS RI: Honors Seminar in Economics ECO 4935 3
BUS Health Research Methods HSA 4700 3
BUS Operations Management Applications MAN 4504 3
BUS Data Management and Analysis with Excel QMB 3302 3
BUS Quantitative Methods in Administration QMB 3600 3
EDU Multidisciplinary Introduction to Research EDF 2910 1
EDU Multidisciplinary Research Methods 1 EDF 2911 1
EDU Education in a Multicultural Society EDF 3610 3
EDU Responsible Conduct of Research EDG 4361 2
ENG Experimental Design and Data Analysis CAP 2753 3
HON Honors Research Methods in Cultural Anthropology ANT 4495 3
HON Honors Introduction to Programming for Visual Art ART 3657C 4
HON Honors Game Studies ART 4640 4
HON Honors 3D Computer Game Development ART 4653C 4
HON Honors Introduction to Data Science COP 3076 3
HON Honors Religion and Politics in Latin America CPO 4305 3
HON Honors Econometrics: Applied Regression Analysis ECO 4412 3
HON Honors Interdisciplinary Critical Inquiry Seminar IDS 3632 1-3
HON Honors Computational Social Science ISS 4304 3
HON Honors General Microbiology MCB 3020 3
HON Honors General Microbiology Lab MCB 3020L 1
HON Honors Cell Biology PCB 4102 4
HON RI: Honors Research Methods in Psychology PSY 3213 3
HON Honors Research Methods in Psychology Lab PSY 3213L 1
NUR Nursing Research NUR 4165 3
SCI Biochemistry 1 BCH 3033 3
SCI Plant Physiology Lab BOT 4503L 2
SCI Plant Biotechnology BOT 4734C 3
SCI Life of a Biologist BSC 2844 1
SCI Introduction to Biological Research BSC 3453 1
SCI Biological Research Writing BSC 3481 2
SCI Honors Research BSC 4917 3
SCI Honors Thesis BSC 4918 3
SCI Special Topics BSC 4930 1-3
SCI Comparative Animal Behavior CBH 4024 3
SCI Organic Chemistry 1 CHM 2210 3
SCI Quantitative Analysis CHM 3120 2
SCI Introduction to Physical Chemistry CHM 3400 3
SCI Inorganic Chemistry CHM 3609 3
SCI Critical Thinking in Environmental Science EVS 4021 3
SCI Introduction to Undergraduate Research 1 IDS 1911 1
SCI Introduction to Undergraduate Research 2 IDS 1913 1
SCI Fundamentals of Research and Inquiry IDS 3910 1
SCI Introduction to Undergraduate Research and Design IDS 3911 1
SCI Applied Mathematical Modeling MAP 4103 3
SCI Issues in Human Ecology PCB 3352 3
SCI Genetics Lab PCB 4067L 3
SCI Comparative Animal Physiology Lab PCB 4723L 1
SCI Cellular Neuroscience and Disease PCB 4842 3
SCI Research Methods in Psychology PSY 3213 3
SCI Experimental Design and Statistical Inference PSY 3234 3
SCI Introduction to Animal Locomotion ZOO 4373
SWCJ Methods of Research in Criminal Justice CCJ 4700 3
SWCJ Research Methods in Social Work SOW 4403 3



Graduate Programs

Data Science and Analytics
Master of Science (M.S.)

Data Science via Scientific Inquiry Concentration
Data Science and Engineering Concentration
Data Science in Business Concentration
Data Science in Society Concentration

The Master of Science with Major in Data Science and Analytics (MSDSA) is a multi-college interdisciplinary program jointly administered by the Department of Mathematics and Statistics in the Charles E. Schmidt College of Science, the Department of Electrical Engineering and Computer Science in the College of Engineering and Computer Science, the Department of Information Technology and Operations Management in the College of Business and the Department of Political Science in the Dorothy F. Schmidt College of Arts and Letters. The program aims to prepare students with essential skill sets needed to analyze small, fast, big, massive and complex data. To allow for maximum flexibility in career aspirations, students may select from four concentrations:

Admission Requirements
To be admitted to the MSDSA program, applicants must:

  1.  Have obtained a bachelor's degree from an accredited institution and possess a minimal background consisting of MAC 2233 (Methods of Calculus) or equivalent and STA 2023 (Introductory Statistics) or equivalent. Students applying to the Data Science and Engineering concentration must have completed a college-level introductory programming course with a minimum grade of "C." Knowledge of Python and statistical packages such as R, as well as coursework in linear algebra are recommended for all concentrations;
  2. Have an undergraduate GPA of 3.0 or higher in the last 60 credits of undergraduate coursework;
  3. Submit two letters of recommendation for all concentrations, except the Data Science and Engineering concentration;
  4. Have attained scores of at least 151 (verbal) and 151 (quantitative) on the Graduate Record Examination (GRE). GRE scores more than five years old are not acceptable normally. GRE is not required for admission to the Data Science and Engineering concentration;
  5. Be proficient in written and spoken English. International students from non-English-speaking countries must present a score of at least 500 (paper-based test) or 213 (computer-based test) or 79 (internet-based test) on the Test of English as a Foreign Language (TOEFL) or a score of at least 6.0 on the International English Language Testing System (IELTS); and
  6. Meet other requirements of the FAU Graduate College.

Curriculum Requirements
The MSDSA program offers both thesis and non-thesis options. Both options require a minimum of 30 credits. Students are required to take one common core course, two additional core courses, four concentration courses and three elective courses for the total of 30 credits. The exact courses taken are to be determined by the students and their advisory committee. The thesis option requires only one elective course and 6 thesis credits. Students selecting the thesis option must complete and defend a written thesis successfully.

Data Science via Scientific Inquiry Concentration

Common Core Courses
Introduction to Data Science CAP 5768 3
Biostatistics STA 5195 3
Take one additional core course
Data Mining and Machine Learning CAP 6673 3
Introduction to Business Analytics and Big Data ISM 6404 3 or
Quantitative Methods in Political Science  POS 6746 3
Take four concentration courses
Computer Data Security CIS 6370 3
Data Analysis and Modeling for Cybersecurity CAI 6803 3
Introduction to Cryptology and Information Security MAD 5474 3
Graph Theory MAD 6307 3
Cryptanalysis MAD 6478 3
Applied Computational Topology MTG 6329 3
Statistical Computing STA 6106 3
Survival Analysis STA 6177 3
Regression Analysis STA 6236 3
Mathematical Statistics STA 6326 3
Applied Time Series Analysis STA 6857 3
Take three elective courses from the Electives Table. Thesis option requires only one elective course and 6 thesis credits.


Data Science and Engineering Concentration (This concentration is also available fully online.)

Common Core Courses
Introduction to Data Science CAP 5768 3
Data Mining and Machine Learning CAP 6673 3
Take one additional core course
Biostatistics STA 5195 3 or
Introduction to Business Analytics and Big Data ISM 6404 3 or
Quantitative Methods in Political Science  POS 6746 3
Take four concentration courses, any course with the prefix CAP offered by the EECS Department, or CEN 6405
Take three elective courses from the Electives Table. Thesis option requires only one elective course and 6 thesis credits.


Data Science in Business Concentration

Common Core Courses
Introduction to Data Science CAP 5768 3
Introduction to Business Analytics and Big Data ISM 6404 3
Take one additional core course
Biostatistics STA 5195 3 or
Data Mining and Machine Learning CAP 6673 3 or
Quantitative Methods in Political Science  POS 6746 3
Take four concentration courses
Quantitative Communication Research COM 6316 3
Data Mining and Predictive Analytics ISM 6136 3
Database Management Systems ISM 6217 3
Advanced Business Analytics ISM 6405 3
Social Media and Web Analytics ISM 6555 3
Data Management and Analysis with Excel QMB 6303 3
Data Analysis for Managers QMB 6603 3
Take three elective courses from the Electives Table. Thesis option requires only one elective course and 6 thesis credits.


Data Science in Society Concentration

Common Core Courses
Introduction to Data Science CAP 5768 3
Quantitative Methods in Political Science  POS 6746 3
Take one additional core course
Biostatistics STA 5195 3 or
Data Mining and Machine Learning CAP 6673 3 or
Introduction to Business Analytics and Big Data ISM 6404 3
Take four concentration courses
Advanced Anthropological Research 2 ANG 6092 3
Quantitative Reasoning in Anthropological Research ANG 6486 3
Social Networks and Big Data Analytics CAP 6315 3
Quantitative Communication Research COM 6316 3
Social Media and Web Analytics ISM 6555 3
Seminar in Political Behavior POS 6208 3
Research Design in Political Science POS 6736 3
Seminar in Advanced Research Methods SYA 6305 3
Take three elective courses from the Electives Table. Thesis option requires only one elective course and 6 thesis credits.


Electives Table

Business Analytics
Data Mining and Predictive Analytics ISM 6136 3
Database Management Systems ISM 6217 3
Introduction to Business Analytics and Big Data ISM 6404 3
Advanced Business Analytics ISM 6405 3
Social Media and Web Analytics ISM 6555 3
Data Management and Analysis with Excel QMB 6303 3
Data Analysis for Managers QMB 6603 3
Database and Cloud Computing
Multiprocessor Architecture CDA 6132 3
Cloud Computing CEN 5086 3
New Directions in Database Systems COP 6726 3
Theory and Implementation of Database Systems COP 6731 3
Database Management Systems ISM 6217 3
Data Mining and Machine Learning
Introduction to Neural Networks CAP 5615 3
Social Networks and Big Data Analytics CAP 6315 3
Data Mining for Bioinformatics CAP 6546 3
Machine Learning for Computer Vision CAP 6618 3
Deep Learning CAP 6619 3
Reinforcement Learning CAP 6629 3
Artificial Intelligence CAP 6635 3
Data Mining and Machine Learning CAP 6673 3 or
Applied Machine Learning CAP 6610 3
Information Retrieval CAP 6776 3
Web Mining CAP 6777 3
Advanced Data Mining and Machine Learning CAP 6778 3
Big Data Analytics with Hadoop CAP 6780 3
Computational Advertising and Real-Time Analytics CAP 6807 3
Computer Performance Modeling CEN 6405 3
Data Mining and Predictive Analytics ISM 6136 3
Data Security and Privacy
Computer Data Security CIS 6370 3
Data Analysis and Modeling for Cybersecurity CAI 6803 3
Management of Information Assurance and Security ISM 6328 3
Introduction to Cryptology and Information Security MAD 5474 3
Cryptanalysis MAD 6478 3
Quantum Mechanics 2 PHY 6646 3
Scientific Applications and Modeling
Photogrammetry and Aerial Photography Interpretation GIS 6028C 3
LiDAR Remote Sensing and Applications GIS 6032C 3
Web GIS GIS 6061C 3
Geospatial Databases GIS 6112C 3
Hyperspectral Remote Sensing GIS 6127 3
Spatial Data Analysis GIS 6306 3
Special Topics (Quantum Information Processing) PHY 6938 3
Computational Physics PHZ 5156 3
Numerical Relativity PHZ 7609 3
Social Data Science
Advanced Anthropological Research 1 ANG 6090 3
Advanced Anthropological Research 2 ANG 6092 3
Quantitative Reasoning in Anthropological Research ANG 6486 3
Social Networks and Big Data Analytics CAP 6315 3
Quantitative Communication Research COM 6316 3
Quantitative Methods in Political Science  POS 6746 3
Research Design in Political Science POS 6736 3
Seminar in Advanced Research Methods SYA 6305 3
Statistics and Data Applications
Biomedical Data and Informatics BSC 6459 3
Biostatistics STA 5195 3
Statistical Computing STA 6106 3
Survival Analysis STA 6177 3
Biostatistics - Longitudinal Data Analysis STA 6197 3
Applied Statistical Methods STA 6207 3
Regression Analysis STA 6236 3
Mathematical Statistics STA 6326 3
Applied Time Series Analysis STA 6857 3
Applied Computational Topology MTG 6329 3

 

Information Technology and Management
Master of Science (M.S.)

Advanced Information Technology Concentration
Business Analytics Concentration
Computer Science Data Analytics Concentration
Cybersecurity Concentration
Information Technology Management Concentration

The Master of Science with Major in Information Technology and Management (MSITM) is jointly offered by the Department of Electrical Engineering and Computer Science (EECS) in the College of Engineering and Computer Science and the Department of Information Technology and Operations Management (ITOM) in the College of Business. Designed for highly motivated individuals with computing and/or managerial backgrounds, the program aims to prepare students for a management career in the area of information technology in organizations. To allow for maximum flexibility in career aspirations, students can select from five concentrations: Advanced Information Technology, Business Analytics, Computer Science Data Analytics, Cybersecurity, and Information Technology Management. The program is offered in person with the Business Analytics and the Information Technology Management concentrations offered in person and fully online. 

Admission Requirements
To be admitted to the MSITM program applicants must have:

  1. An undergraduate degree in Computer Science, Information Engineering Technology or an IT-related field of study. Applicants with another undergraduate degree and documented work experience of two or more years in an IT function will be evaluated as well;
  2. An undergraduate GPA of 3.0 or higher;
  3.  GRE or GMAT scores more than five years old are normally not acceptable. The GRE and the GMAT requirement is waived for any student who has a baccalaureate degree from either FAU's Department of Electrical Engineering and Computer Science (EECS) or FAU's Department of Information Technology and Operations Management (ITOM) with a GPA of at least 3.25 (out of a possible 4.0) in the last 60 credits attempted prior to graduation. GRE/GMAT is not required for admission to the Advanced Information Technology Concentration, Computer Science Data Analytics Concentration, and Cybersecurity Concentration;
  4. International students from non-English-speaking countries must be proficient in written and spoken English as evidenced by a score of at least 500 (paper-based test) or 213 (computer-based test) or 79 (Internet-based test) on the Test of English as a Foreign Language (TOEFL) or a score of at least 6.0 on the International English Language Testing System (IELTS); and
  5. Meet other requirements of the FAU Graduate College.

Degree Requirements
Students in all concentrations are required to complete 30 graduate credits, or ten, 3-credit courses (5000 level or higher), with a 3.0 GPA or better to graduate.  

Students in the Advanced Information Technology, Computer Science Data Analytics, and Cybersecurity concentrations will be awarded the degree by the College of Engineering and Computer Science, while those in the Information Technology Management and Business Analytics concentrations will have their degrees awarded by the College of Business. For more information about the Master of Science in Information Technology and Management degree program, call the Department of Electrical Engineering and Computer Science at 561-297-3482, or email ceecs@bydsatelier.com.

Advanced Information Technology Concentration (30 credits)

Students are required to take the following three courses:
Software Engineering CEN 5035
Theory and Implementation of the Database Systems COP 6731
Management of Information Systems and Technology ISM 6026

In addition, students must take five electives from graduate courses with prefixes CAP, CDA, CEN, CIS, COP, COT and CNT offered by the Department of Electrical Engineering and Computer Science (EECS).
The last two electives must be chosen from the following ITOM courses:
Mobile Apps for Business ISM 6058
Data Mining and Predictive Analytics ISM 6136
Information Technology Project and Change
Management		 ISM 6316
Management of Information Assurance and Security ISM 6328
Enterprise Information Technology Service
Management		 ISM 6368
Advanced Business Analytics ISM 6405
Business Innovation with Artificial Intelligence ISM 6427C
Blockchain and Crypto Assests: Digital Business Transformation ISM 6455
Web-Based Business Development ISM 6508
Information Technology Sourcing Management ISM 6509
Social Media and Web Analytics ISM 6555
Special Topics ISM 6930
Data Management and Analysis with Excel QMB 6303

 

Information Technology Management Concentration (30 credits)

Students are required to take the following six courses offered by the College of Business:
Management of Information Systems and
Technology		 ISM 6026
Information Technology Project and Change
Management		 ISM 6316
Management of Information Assurance and Security ISM 6328
Web-Based Business Development ISM 6508
Information Technology Sourcing Management ISM 6509
Communication Strategies for Business Professionals and Core-Course Follow-Up GEB 6215
Students must take one elective from the following ITOM courses:
Mobile Apps for Business ISM 6058
Data Mining and Predictive Analytics ISM 6136
Enterprise Information Technology Service
Management		 ISM 6368
Advanced Business Analytics ISM 6405
Business Innovation with Artificial Intelligence ISM 6427C
Blockchain and Crypto Assests: Digital Business Transformation ISM 6455
Social Media and Web Analytics ISM 6555
Special Topics ISM 6930
Data Management and Analysis with Excel QMB 6303
In addition, students must take three electives from graduate courses with prefixes CAP, CDA, CEN, CIS, COP, COT and CNT offered by the Department of Electrical Engineering and Computer Science (EECS).


Computer Science Data Analytics Concentration (30 credits)

Students are required to take the following three courses offered by the Electrical Engineering and Computer Science (EECS) Department:
Introduction to Data Science CAP 5768
Software Engineering CEN 5035
Theory and Implementation of the Database Systems COP 6731
In addition, students must take four EECS Department electives as follows: two graduate courses with the prefix CAP and two graduate courses with prefixes CAP, CDA, CEN, CIS, COP, COT and CNT.

The last three electives must be chosen from the following ITOM courses:
Data Mining and Predictive Analytics ISM 6136
Database Management Systems ISM 6217
Introduction to Business Analytics and Big Data ISM 6404
Advanced Business Analytics ISM 6405
Business Innovation with Artificial Intelligence ISM 6427C
Social Media and Web Analytics ISM 6555
Special Topics ISM 6930
Data Management and Analysis with Excel QMB 6303
Data Analysis for Managers QMB 6603


Note: Students in this concentration may satisfy the requirements for the Big Data Analytics certificate. Follow up with the EECS advisor to see if the student meets all the requirements for the certificate.

Business Analytics Concentration (30 credits)

Students are required to take the following six courses offered by the College of Business:
Management of Information Systems and Technology ISM 6026
Data Mining and Predictive Analytics ISM 6136
Introduction to Business Analytics and Big Data ISM 6404
Business Innovation with Artificial Intelligence ISM 6427C
Advanced Business Analytics ISM 6405 or
Social Media and Web Analytics ISM 6555
Communication Strategies for Business Professionals and Core-Course Follow-Up GEB 6215
Students must take one elective from the following ITOM courses:
Mobile Apps for Business ISM 6058
Information Technology Project and Change Management ISM 6316
Management of Information Assurance and Security ISM 6328
Enterprise Information Technology Service Management ISM 6368
Blockchain and Crypto Assests: Digital Business Transformation ISM 6455
Web-Based Business Development ISM 6508
Information Technology Sourcing Management ISM 6509
Special Topics ISM 6930
Data Management and Analysis with Excel QMB 6303
In addition, students must take three electives from the EECS Department as follows: two graduate courses with the prefix CAP and one graduate course with prefixes CAP, CDA, CEN, CIS, COP, COT and CNT.


Cybersecurity Concentration (30 credits) 

Students are required to take the following three courses:
Software Engineering CEN 5035
Theory and Implementation of the Database Systems COP 6731
Management of Information Systems and Technology ISM 6026
Students must take three cybersecurity courses from the list below. Course substitution is allowed with the advisor's prior approval.
Cryptographic Engineering CDA 5326
Practical Aspects of Modern Cryptography CIS 5371
Computer Data Security CIS 6370
Distributed Systems Security CIS 6375
Cryptocurrencies and Blockchain Technologies CIS 6730
Secret Sharing Protocols COT 6427
Data Analysis and Modeling for Cybersecurity CAI 6803
Students must take two Electrical Engineering and Computer Science (EECS) courses wth prefixes of CAP, CDA, CEN, CIS, COP, COT, CTS or CNT offered by the EECS department.
The last two electives must be chosen from the following Information Technology and Operations Management (ITOM) courses:
Management of Information Assurance and Security ISM 6328
Digital Forensics Management ISM 6376
Business Innovation with Artificial Intelligence ISM 6427C
Blockchain and Cryto Assets: Digital Business Transformation ISM 6455
Special Topics ISM 6930

 

Informational Technology and Management
Master of Science (M.S.)
Professional Program

Advanced Information Technology Concentration
Business Analytics Concentration
Computer Science Data Analytics Concentration
Information Technology Management Concentration

The Professional Master of Science with major in Information Technology and Management is a self-supporting program offered jointly by the Department of Electrical Engineering and Computer Science in the College of Engineering and Computer Science and the Department of Information Technology and Operations Management in the College of Business. This program is designed for working professionals. It offers four concentrations and requires 30 credits. Degree requirements are listed in the tables below. The program is offered in person with the Business Analytics and the Information Technology Management concentrations offered in person and fully online.

Advanced Information Technology Concentration (30 credits)

Students are required to take the following three courses:
Software Engineering CEN 5035
Theory and Implementation of the Database Systems COP 6731
Management of Information Systems and Technology ISM 6026
In addition, students need to take six electives from the graduate courses with prefixes CAP, CDA, CEN, CIS, COP, COT and CNT offered by the Department of Electrical Engineering and Computer Science (EECS).
Lastly, one elective course must be chosen from the following ITOM courses:
Mobile Apps for Business ISM 6058
Data Mining and Predictive Analytics ISM 6136
Information Technology Project and Change
Management		 ISM 6316
Management of Information Assurance and Security ISM 6328
Enterprise Information Technology Service
Management		 ISM 6368
Advanced Business Analytics ISM 6405
Business Innovation with Artificial Intelligence ISM 6427C
Blockchain and Crypto Assests: Digital Business Transformation ISM 6455
Web-Based Business Development ISM 6508
Information Technology Sourcing Management ISM 6509
Social Media and Web Analytics ISM 6555
Special Topics ISM 6930
Data Management and Analysis with Excel QMB 6303

 

Information Technology Management Concentration (30 credits)

Students are required to take the following six courses offered by the College of Business:
Management of Information Systems and
Technology		 ISM 6026
Information Technology Project and Change
Management		 ISM 6316
Management of Information Assurance and Security ISM 6328
Web-Based Business Development ISM 6508
Information Technology Sourcing Management ISM 6509
Communication Strategies for Business Professionals GEB 6217
Students must take two electives from the following ITOM courses:
Mobile Apps for Business ISM 6058
Data Mining and Predictive Analytics ISM 6136
Enterprise Information Technology Service
Management		 ISM 6368
Advanced Business Analytics ISM 6405
Business Innovation with Artificial Intelligence ISM 6427C
Blockchain and Crypto Assests: Digital Business Transformation ISM 6455
Social Media and Web Analytics ISM 6555
Special Topics ISM 6930
Data Management and Analysis with Excel QMB 6303
In addition, students must take two electives from graduate courses with prefixes CAP, CDA, CEN, CIS, COP, COT and CNT offered by the Department of Electrical Engineering and Computer Science (EECS).

 

Computer Science Data Analytics Concentration (30 credits)

Students are required to take the following three courses offered by the Electrical Engineering and Computer Science (EECS) Department:
Introduction to Data Science CAP 5768
Software Engineering CEN 5035
Theory and Implementation of the Database Systems COP 6731
In addition, students must take five EECS department electives as follows: two graduate courses with the prefix CAP and three graduate courses with prefixes CAP, CDA, CEN, CIS, COP, COT and CNT.
The last two electives must be chosen from the following ITOM courses:
Data Mining and Predictive Analytics ISM 6136
Database Management Systems ISM 6217
Introduction to Business Analytics and Big Data ISM 6404
Advanced Business Analytics ISM 6405
Business Innovation with Artificial Intelligence ISM 6427C
Social Media and Web Analytics ISM 6555
Special Topics ISM 6930
Data Management and Analysis with Excel QMB 6303
Data Analysis for Managers QMB 6603


Note: Students in th is concentration may satisfy the requirements for the Big Data Analytics certificate. Follow up with the EECS advisor to see if the student meets all the requirements for the certificate.

Business Analytics Concentration (30 credits)

Students are required to take the following seven courses offered by the College of Business:
Management of Information Systems and Technology ISM 6026
Data Mining and Predictive Analytics ISM 6136
Introduction to Business Analytics and Big Data ISM 6404
Advanced Business Analytics ISM 6405
Business Innovation with Artificial Intelligence ISM 6427C
Social Media and Web Analytics ISM 6555
Communication Strategies for Business Professionals GEB 6217
Students must take one elective from the following ITOM courses:
Mobile Apps for Business ISM 6058
Information Technology Project and Change Management ISM 6316
Management of Information Assurance and Security ISM 6328
Enterprise Information Technology Service Management ISM 6368
Blockchain and Crypto Assests: Digital Business Transformation ISM 6455
Web-Based Business Development ISM 6508
Information Technology Sourcing Management ISM 6509
Special Topics ISM 6930
Data Management and Analysis with Excel QMB 6303
In addition, students must take two electives from the EECS department as follows:one graduate course with the prefix CAP and one graduate course with prefixes CAP, CDA, CEN, CIS, COP, COT and CNT.

 

Neuroscience
Doctor of Philosophy (Ph.D.)

(Minimum of 72 credits required)

The Neuroscience Graduate doctoral program (NGP) is a multi-college, multi-institute interdisciplinary degree program organized in partnership with the FAU Brain Institute. Graduate-level instruction is provided by faculty in multiple departments located in the Charles E. Schmidt College of Science, the Charles E. Schmidt College of Medicine, the College of Engineering and Computer Science, the College of Education and the Harriet L. Wilkes Honors College. Affiliated faculty from the Max Planck Florida Institute for Neuroscience and Scripps Research Florida also participate in the program.

The program aims to equip students with the advanced conceptual and technical skills needed to forge productive, neuroscience-oriented careers in industry, academia and government. To allow for maximum flexibility in career aspirations, students have the opportunity to pursue thesis research in laboratories located in any of the Colleges and Institutes noted above. Program faculty have expertise in a broad range of research areas, including cellular and molecular neuroscience, cognitive and behavioral neuroscience, computational neuroscience, synaptic plasticity, brain development, learning and memory, neuroimmunology, auditory and speech neuroscience, visual neuroscience and neurology. The work is directed at understanding the mechanisms underlying neurodegeneration, stroke, autism, epilepsy, depression, sleep disorders and drug addiction, in order to advance effective treatments.

Admission Standards
The program seeks to admit applicants who are academically excellent and have completed an undergraduate or M.S. degree demonstrating substantial training in the biological sciences, psychology, or engineering and computer sciences. Recommended preparation includes upper-division courses in biology (molecular/cellular biology, genetics, physiology), psychology (animal and human behavior, learning and memory, cognition), chemistry (organic chemistry, biochemistry), mathematics (statistics and calculus) and computer engineering and programing. Prior coursework in neuroscience is desirable, and evidence of prior research experience is particularly important. A competitive applicant usually will have prior research experience and should describe their research experience in the Statement of Purpose/Personal Statement.

Admission Requirements
All students must meet the minimum graduate admission requi rements of the University. Refer to the Prospective Students and Admissions sections on the Graduate College website. Additional requirements are:

  1. Completion of a bachelor’s or M.S. degree from a regionally accredited institution in an appropriate major, prior to anticipated start date in the Ph.D. program.
  2. Minimum GPA of 3.40 as an undergraduate and/or M.S. student.
  3. Complete sets of transcripts from all previous collegiate institution(s) attended.
  4. A minimum of three letters of recommendation, preferably from instructors and advisors who are familiar with the applicant’s recent academic and research experiences.
  5. An essay of Purpose/Interests in the form of a Personal Statement.
  6. GRE scores are optional.
  7. International students whose native language is not English must score at least 79-80 (Internet-based test) on the Test of English as a Foreign Language (TOEFL). Satisfactory TOEFL scores can offset verbal GRE scores at the discretion of the program's Recruitment Committe e. Additionally, international students whose transcripts are from non-U.S. institutions must have their credentials evaluated course-by-course. International students must also demonstrate competency in spoken English.

Previous graduate coursework may be applied toward the course requirements of the Neuroscience Ph.D. Students may receive up to 15 credits earned beyond the baccalaureate degree, including up to 9 credits of Core course credit, not to include Laboratory Rotations and Neuroscience Seminar, based on comparable courses taken prior to admission. Transfer credits must be approved by the Prog ram Steering Committ ee and the Graduate College. Evaluation of transfer credits will be based on content and will require an official copy of each course syllabus for assessment.

Degree Requirements
The Doctor of Philosophy with Major in Neuroscience is a research-intensive degree requiring a minimum of
72 credits beyond the baccalaureate degree. The following are specific requirements for this degree:

  1. Completion of 21 core credits listed in Required Core Courses.
  2. Completion of 9 elective credits from the courses listed in Elective Courses.
  3. Completion of 24 dissertation credits.
  4. The remaining 18 credits may include elective coursework at the 6000-level or above, advanced research or dissertation research credits that support the student's research plan with approval of the student's Ph.D. supervisor.
  5. Completion of Neuroscience Ph.D. Lab Rotations, representing eight-week research internships in different laboratories during the fall and spring semesters of Year 1.
  6. Acceptance into the laboratory of an approved program faculty member for thesis research by the end of the spring semester of Year 1.
  7. Achievement of a “B” or higher grade in all courses, with an overall GPA o f at least 3.0 main tained.
  8. With the exception of Neuroscience Seminar and Laboratory Rotations, no core or elective courses can be taken with the option of satisfactory/unsatisfactory grading.
  9. Students must enroll in the Neuroscience Seminar each fall and spring semester for the entire time they remain in program, with the expectation that most students will graduate in five years. Starting in Year 2, the Neuroscience Seminar will be taken for 0 credit.
  10. Admission to Ph.D. candidacy requires the writing and successful public defense of an original dissertation research proposal.
  11. Degree completion requires the writing and successful public defense of a dissertation describing the context, approach, results and impact of thesis research.
  12. Students are expected to publish at least one peer-reviewed research paper as first author involving research activities described in their thesis proposal prior to degree completion.

Required Core Courses
Brain Diseases: Mechanisms and Therapy BMS 6736 3
Scientific Communication BSC 6846 3
Neuroscience Seminar*
(fall and spring of Year 1) 		PSB 6920 2
Cellular and Molecular Neuroscience PSB 6345 3
Systems and Integrative Neuroscience PSB 6346 3
Neuroscience Ph.D. Lab Rotation
(fall and spring of Year 1) 		PSB 6910L 4
Experimental Design 1** PSY 6206 3 or
Computational Neuroscience 1** ISC 6460 3
Required Core credits 21
   
Dissertation PSB 7980 24
     
Elective Courses (some may have prerequisites)
Choose at least three courses from the list
Bioinformatics: Bioengineering Perspectives BME 6762 3
Practical Cell Neuroscience BSC 6417C 3
Biomedical Data and Informatics BSC 6459 3
Introduction to Neural Networks CAP 5615 3
Introduction to Data Science CAP 5768 3
Foundations of Vision CAP 6411 3
Data Mining for Bioinformatics CAP 6546 3
Artificial Intelligence CAP 6635 3
Data Mining and Machine Learning CAP 6673 3
Biosignal Processing EEE 5286 3
Seminar in Human Perception EXP 6208 3
Seminar in Cognition EXP 6609 3
Special Topics in Cognition (such as Attention and Consciousness, Machine Perception and Cognitive Robotics) EXP 6930 3
Neural Plasticity GMS 6021 3
Principles of Neuroimmunology GMS 6708 3
Nonlinear Dynamical Systems ISC 5453 3
Cognitive Neuroscience ISC 5465 3
Methods in Complex Systems ISC 6450 3
Computational Neuroscience 1 ISC 6460 3
Neurobiology of Addiction PCB 5844 3
Advanced Cell Physiology PCB 6207 3
Neurophysiology PCB 6835C 3
Adult Neurogenesis PCB 6848 3
Advanced Neurophysiology Lab PCB 6837L 3
Seminar in Behavioral Neuroscience PSB 6058 3
Developmental Neurobiology PSB 6515 3
Developmental Neuropsychology PSB 6516 3
Special Topics in Behavioral Neuroscience (such as Functional Neuroanatomy) PSB 6930 3
Experimental Design 2 PSY 6207 3
Special Topics (such as Neuroscience of Sleep) PSY 6930 3
Neural Bases of Human Communication SPA 5107 3
Adult Language Disorders SPA 6410 3
Genetics of Communication Disorders SPA 6438 3
Biostatistics STA 5195 3
Human Neuroanatomy ZOO 6748 3
Electives credits 9
Additional elective coursework at the 6000 level or above, advanced research or dissertation credits that support the student's research plan 18
Total 72


* Neuroscience Seminar (PSB 6920) is taken in the fall and spring of Year 1 for 1 credit per semester. In later years, it is taken for 0 credit every fall and spring semester.

** Students must either take Experimental Design 1 (PSY 6206) or Computational Neuroscience 1 (ISC 6460), but need not take both.

Supervisory Committee Requirements
By mutual agreement, students identify their final Ph.D. supervisor and research lab before the end of the spring semester of Year 1. A Supervisory Committee, including the Ph.D. supervisor and three other graduate faculty, knowledgeable in aspects of the project, is assembled during the fall of Year 2. Students are encouraged to include on their committee one faculty-level member who is not a member of the Neuroscience Graduate Program, including graduate faculty from other institutions. The Ph.D. supervisor serves as the chair of the Supervisory/Dissertation Advisory Committee, except when the supervisor is an affiliate FAU faculty member at the Max Planck Florida Institute or the Scripps Research Institute Florida. The chair of the committee must have a full-time appointment at FAU, with affiliate faculty serving as co-chairs.

Qualifying Exam and Proposal Defense
Students in the Neuroscience doctoral program must prepare a written grant proposal modeled on NIH or NSF templates for predoctoral fellowship applications. The proposal will be targeted to their chosen area of research. Students will present their proposal orally in an open forum advertised to the University community, followed by an oral examination consisting of questions from the student’s Supervisory Committee. Following the defense, committee members vote to either pass, pass with conditions, or fail the student. If passed with conditions, students must be able to satisfy any conditions set by the committee within three months prior to resubmission of their proposal for a second oral examination.

Doctoral Dissertation Defense
Students in the Neuroscience doctoral program will develop a written dissertation following the format required by the Graduate College, present the findings of their research orally in a forum open and advertised to the public, followed by an oral examination by the student’s Dissertation Committee. Following the defense, committee members vote to either pass, pass with conditions, or fail the student. Students must satisfy any conditions imposed by the committee within three months prior to resubmission of their proposal for a second oral examination. The committee shall determine whether the student passes or fails the thesis defense examination and allows for a re-examination following the rules of the Graduate College.

Graduate Certificates

Big Data Analytics
Graduate Certificate

(Minimum of 12 credits required)

The digital age is here to stay. Organizations now own and have access to unfathomable amounts of data. New technologies and efforts are needed to move on to the next phase of the digital revolution - the data revolution. To provide students with the knowledge necessary in this age of Big Data, the Department of Electrical Engineering and Computer Science (EECS) and the Department of Information Technology and Operations Management (ITOM) have jointly designed the Big Data Analytics graduate certificate. This 12-credit certificate allows graduate students to expand their knowledge and skills in the concepts, technologies, and tools of business intelligence, data analytics and business analytics and be recognized for their achievement. The certificate program has two tracks: Computer Science (CS), which is also available fully online, and Business (BU).

Tracks
CS Track: The Big Data Analytics certificate with a track in Computer Science will be granted to a student who completes three 3-credit courses from the CS Data Analytics course list and one 3-credit course from the ITOM Business Analytics course list.

BU Track: The Big Data Analytics certificate with a track in Business will be granted to a student who completes three 3-credit courses from the ITOM Business Analytics course list and one 3-credit course from the CS Data Analytics course list.

Admission
CS Track: Open to students who have a B.S. degree in Computer Science or in a related field of Science or Engineering and a GPA of at least 3.0. Students must satisfy the prerequisites for each course in the program. All four courses must be completed with a GPA of 3.0 or better. All course materials are in English; all international students must demonstrate proficiency in English to enter the program.

BU Track: Open to students who have a bachelor's degree in Business or in a related field and a GPA of at least 3.0. Students must satisfy the prerequisites for each course in the program. All four courses must be completed with a GPA of 3.0 or better. All course materials are in English; all international students must demonstrate proficiency in English to enter the program.

Big Data Analytics Courses by Track

CS Data Analytic Courses
Select three from this list and one from the list of ITOM courses.
Introduction to Neural Networks CAP 5615 3
Introduction to Data Science CAP 5768 3
Social Networks and Big Data Analytics CAP 6315 3
Data Mining for Bioinformatics CAP 6546 3
Applied Machine Learning CAP 6610 3
Deep Learning CAP 6619 3
Data Mining and Machine Learning CAP 6673 3
Information Retrieval CAP 6776 3
Web Mining CAP 6777 3
Advanced Data Mining and Machine Learning CAP 6778 3
Big Data Analytics with Hadoop CAP 6780 3
Computer Performance Modeling CEN 6405 3
Deep Learning CAP 6619 3
Computational Advertising and Real-Time Data Analytics CAP 6807 3
ITOM Business Analytics Courses
Select three from this list and one from the list of CS courses.
Data Mining and Predictive Analytics ISM 6136 3
Database Management Systems ISM 6217 3
Introduction to Business Analytics
and Big Data		 ISM 6404 3
Advanced Business Analytics ISM 6405 3
Business Innovation with Artificial Intelligence ISM 6427C 3
Social Media and Web Analytics ISM 6555 3
Data Management and Analysis with Excel QMB 6303 3
Data Analysis for Managers QMB 6603 3

 

Big Data Analytics
Graduate Certificate
Professional Program

(Minimum of 12 credits required)

The Professional Big Data Analytics certificate is designed for working professionals currently enrolled in self-supporting programs in the College of Business or College of Engineering and Computer Science. This is a stand-alone certificate tailored for working professionals and alumni with graduate degrees who are looking for specialized knowledge in Big Data Analytics. The certificate consists of 12 credits offered jointly by the colleges and two tracks from which to choose courses. Tracks and lists of courses are the same as for the Big Data Analytics graduate certificate noted above.

Cyber Security
Graduate Certificate

(Minimum of 12 credits required)

Cybercrime-related issues especially impact the State of Florida because a significant part of the state's economic development comes from tourism, international banking and high-tech industries. The number of scientists, engineers and experts needed with special skills in cyber security exceeds the number available. The Cyber Security certificate provides opportunities for graduate students to expand their knowledge and skills to meet the needs of the cyber security field. Due to their extensive expertise and facilities, the departments of Electrical Engineering and Computer Science (EECS) and Mathematics and Statistics have jointly designed the Cyber Security certificate. This 12-credit certificate program has two tracks: Computer Science (CS), which is also available fully online, and Mathematics (Math).

Tracks
CS Track: The Cyber Security certificate with a track in Computer Science will be granted to a student who completes four 3-credit courses as follows: three 3-credit courses from the CS Cyber Security course list and one 3-credit course from either the CS or the Math Cyber Security course list.

Math Track: The Cyber Security certificate with a track in Mathematics will be granted to a student who completes four 3-credit courses as follows: three 3-credit courses from the Math Cyber Security course list and one 3-credit course from either the Math or the CS Cyber Security course list.

Admission
CS Track: Open to students who have a B.S. degree in Computer Science or in a related field of Science or Engineering and a GPA of at least 3.0. Students must satisfy the prerequisites for each course in the program. All four courses must be completed with a GPA of 3.0 or better. All course materials are in English; all international students must demonstrate proficiency in English to enter the program.

Math Track: Open to students who have a bachelor's degree in mathematics or in a related field and a GPA of at least 3.0. Students must satisfy the prerequisites for each course in the program. All four courses must be completed with a GPA of 3.0 or better. All course materials are in English; all international students must demonstrate proficiency in English to enter the program.

Cyber Security Courses by Track

CS Cyber Security Courses
Select three from this list and one more from this list or the list of Math courses. Additional courses may be used as replacements with prior approval of the EECS Department.
Practical Aspects of Modern Cryptography CIS 5371 3
Computer Data Security CIS 6370 3
Distributed Systems Security CIS 6375 3
Secret Sharing Protocols COT 6427 3
Data Analysis and Modeling for Cybersecurity CAI 6803 3
Math Cyber Security Courses
Select three from this list and one more from this list or the list of CS courses.
Introduction to Cryptology and Information
Security		 MAD 5474 3
Cryptanalysis MAD 6478 3
Coding Theory MAD 6607 3
Number Theory and Cryptography MAS 6217 3


Transportation, Logistics and Supply Chain Management
 Graduate Certificate

(Minimum of 12 credits required)

To provide students with the knowledge necessary in this age of connected supply chains, the Department of Information Technology and Operations Management (ITOM) in the College of Business and the Department of Civil, Environmental and Geomatics Engineering (CEGE) in the College of Engineering and Computer Science offer a jointly designed certificate in Transportation, Logistics and Supply Chain Management. This 12-credit certificate permits graduate students to expand their knowledge on the technical skills of transportation engineering and the analytical business decision-making skills of supply chain management.

Admission
This certificate program is open to students who have a bachelor's degree in business or engineering or in a related field and a GPA of at least 3.0. Students must satisfy the prerequisites for each course in the program.

Curriculum
All four required courses must be completed with a GPA of 3.0 or better. All course materials are in English; all international students must demonstrate proficiency in English to enter the program.

Required Courses by Department
ITOM Department
Select two from the list, one of which must be MAN 6596.
Operations Management MAN 6501 3
Project Management MAN 6581 3
Supply Chain Management MAN 6596 3
CEGE Department
Select two from the list.
Transportation System Analysis TTE 6501 3
Transportation and Supply Chain Systems TTE 6507 3
Maritime Freight Operations TTE 6508 3