The MS in Applied Information Technology is the very best graduate education in IT for high-potential leaders, especially those working on IT solutions that affect the federal government, industry or non-profit. Its objective is to graduate individuals of competence and character who can lead multidisciplinary teams in the design, justification, development, management, and sustainment of mega-systems from data to decision in the private and federal sectors. The MS in AIT provides a high quality curricula for students seeking to pursue their careers in the leading IT areas including Applied Artificial Intelligence Technologies, Cyber Security, Big Data Analytics, Knowledge Mining, Data Analytics in Social Media, and Cyber-Human Interaction.
The MS AIT program offers the Cyber Security, Data Analytics and Intelligence Methods, and Machine Learning Engineering concentration fully online. For the online program, courses are offered in a condensed 8-week format, with students taking one course at a time. Content of courses, objectives, evaluation methods, and outcomes are identical to those for the on-campus program. Only the delivery format is different. The online program is intended to be completed in about 2.5 years. Request additional information for the online program, learn more, or apply.
At the doctoral level, the department offers a concentration in the INFT PhD program.
Admissions
Applicants must have completed a baccalaureate degree from one of the Mason-recognized U.S. institutional accrediting agencies and earned a GPA of 3.00 or better in their 60 highest-level credits. They must be experienced in the fundamentals of IT and quantitative methods. Application Requirements and Deadlines are available from https://cec.gmu.edu/admissions/graduate-admissions/application-requirements-and-deadlines.
High achieving Mason Engineering alumni who has shown exemplary work in an undergraduate degree may consider our Fast-Track graduate admission process which requires fewer supplementary admission materials.
Degree Requirements
Total credits: 30
Completion of the MS program requires a minimum of 30 approved graduate credits (10 courses). To provide a common background in the fundamentals of information sciences and technology, all students are required to complete four core courses. In addition to the core courses, students must choose a concentration within the program by taking six courses from one of the concentration areas listed below.
Students interested in the PhD in IT program must pursue the Applied Artificial Intelligence Technologies, Cyber Security, Data Analytics and Intelligence Methods, Human-Computer Interaction, or Machine Learning Engineering concentrations. They are required to meet with an advisor before applying to the program. In addition, students must take AIT 602 and one of the following courses: AIT 699, AIT 799, or AIT 796, while they are completing their MS AIT degree.
Students in all concentrations may take other CEC graduate-level courses not listed below as part of their MS technical electives subject to prior advisor approval.
Applied Information Technology, MS Requirements
Core Courses
| Code | Title | Credits |
|---|---|---|
| Required Core Courses | 12 | |
| For students in all concentrations except the IT Management concentration: | ||
| Algorithms and Data Structures Essentials | ||
| AI-Augmented Database Management Systems | ||
| Fundamentals of Computing Platforms | ||
| Information: Representation, Processing and Visualization | ||
| For students in the IT Management concentration: | ||
| AI-Augmented Database Management Systems | ||
| Fundamentals of Computing Platforms | ||
| Project Management Concepts and Methods | ||
| Information: Representation, Processing and Visualization | ||
| Total Credits | 12 | |
Available Concentrations
- Applied Artificial Intelligence Technologies (AAIT)
- Cyber Security (CYBR)
- Data Analytics and Intelligence Methods (DAIN)
- IT Management (ITMG)
- Machine Learning Engineering (MLE)
Applied Artificial Intelligence Technologies (AAIT)
| Code | Title | Credits |
|---|---|---|
| Foundation | ||
| Select four courses from the following: | 12 | |
| Foundations of Applied AI | ||
| Foundations of Data Processing | ||
| Information Technology, Ethics, and Society | ||
| AI Application Development | ||
| Electives | ||
| Select two courses from the following: | 6 | |
| Programming Essentials | ||
| Topics in Applied Information Technology | ||
| Introduction to Research in Applied Information Technology | ||
| AI-Driven Big Data Essentials | ||
| Interactive Machine Learning and Artificial Intelligence | ||
| Human-AI Interaction | ||
| Natural Language Processing: Theory and Practice | ||
| Introduction to Applied Machine Learning | ||
| Project Management Concepts and Methods | ||
| Capstone Seminar | ||
| AI and Cybersecurity | ||
| Advanced Topics in Applied Information Technology | ||
| Research Project | ||
| Natural Language Processing with Deep Learning | ||
| Applied Machine Learning | ||
| Advanced Special Topics in Applied Information Technology | ||
| Master's Thesis | ||
| Total Credits | 18 | |
| Code | Title | Credits |
|---|---|---|
| Foundation | ||
| Select four courses from the following: | 12 | |
| Cyber Security Fundamentals | ||
| Cloud Computing Security | ||
| Secure Software Development | ||
| Network and Systems Security | ||
| Electives | ||
| Select two courses from the following: | 6 | |
| Programming Essentials | ||
| Foundations of Applied AI | ||
| Topics in Applied Information Technology | ||
| Introduction to Research in Applied Information Technology | ||
| Information Technology, Ethics, and Society | ||
| Interpretable Machine Learning | ||
| Project Management Concepts and Methods | ||
| Identity and Access Management | ||
| Capstone Seminar | ||
| IoT and Edge Systems | ||
| IoT Security | ||
| AI and Cybersecurity | ||
| Advanced Topics in Applied Information Technology | ||
| Research Project | ||
| Cyber Security: Emerging Threats and Countermeasures | ||
| Incident Handling and Penetration Testing | ||
| Advanced Special Topics in Applied Information Technology | ||
| Master's Thesis | ||
| Total Credits | 18 | |
Data Analytics and Intelligence Methods (DAIN)
| Code | Title | Credits |
|---|---|---|
| Foundation | ||
| Select four courses from the following: | 12 | |
| Foundations of Data Processing | ||
| Metadata Analytics for Big Data | ||
| AI-Driven Big Data Essentials | ||
| Intelligence Analysis Methods | ||
| Data Analytics in Social Media | ||
| Electives | ||
| Select two courses from the following: | 6 | |
| Programming Essentials | ||
| Foundations of Applied AI | ||
| Topics in Applied Information Technology | ||
| Introduction to Research in Applied Information Technology | ||
| Information Technology, Ethics, and Society | ||
| Rapid Information Systems Prototyping | ||
| Knowledge Mining from Big-Data | ||
| Natural Language Processing: Theory and Practice | ||
| Interpretable Machine Learning | ||
| Interaction Design and Accessibility | ||
| Introduction to Applied Machine Learning | ||
| Project Management Concepts and Methods | ||
| Interactive Visualization and Data Analytics | ||
| Capstone Seminar | ||
| Advanced Topics in Applied Information Technology | ||
| Research Project | ||
| Rapid Development of Scalable Applications | ||
| Advanced Human Computer Interaction | ||
| Theories and Models in Geo-Social Data Analytics | ||
| Natural Language Processing with Deep Learning | ||
| Advanced Web Analytics Using Semantics | ||
| Applied Machine Learning | ||
| Applied Deep Learning | ||
| Advanced Special Topics in Applied Information Technology | ||
| Master's Thesis | ||
| Total Credits | 18 | |
Human-Computer Interaction (HCI)
| Code | Title | Credits |
|---|---|---|
| Foundation | ||
| Select four courses from the following: | 12 | |
| Introduction to Human-Computer Interaction | ||
| Introduction to Interaction Design | ||
| Introduction to Research in Applied Information Technology | ||
| Interactive Visualization and Data Analytics | ||
| Advanced Human Computer Interaction | ||
| Electives | ||
| Select two courses from the following: | 6 | |
| Programming Essentials | ||
| Foundations of Applied AI | ||
| Information Technology, Ethics, and Society | ||
| Interactive Machine Learning and Artificial Intelligence | ||
| Human-AI Interaction | ||
| Interaction Design and Accessibility | ||
| Project Management Concepts and Methods | ||
| Capstone Seminar | ||
| Advanced Topics in Applied Information Technology | ||
| Research Project | ||
| Advanced Special Topics in Applied Information Technology | ||
| Master's Thesis | ||
| Accessibility and Assistive Technologies | ||
| Total Credits | 18 | |
IT Management (ITMG)
| Code | Title | Credits |
|---|---|---|
| Foundation | ||
| Select four courses from the following: | 12 | |
| Foundations of Data Processing | ||
| Determining Needs for Complex Big Data Systems | ||
| Cyber Security Fundamentals | ||
| Capstone Seminar | ||
| Electives | ||
| Select two courses from the following: | 6 | |
| Programming Essentials | ||
| Foundations of Applied AI | ||
| Metadata Analytics for Big Data | ||
| Topics in Applied Information Technology | ||
| Information Technology, Ethics, and Society | ||
| Rapid Information Systems Prototyping | ||
| AI-Driven Big Data Essentials | ||
| Advanced Information Security Risk Management | ||
| Cloud Computing Security | ||
| Identity and Access Management | ||
| Intelligence Analysis Methods | ||
| Law and Ethics of Big Data | ||
| IoT and Edge Systems | ||
| Advanced Topics in Applied Information Technology | ||
| Total Credits | 18 | |
Machine Learning Engineering (MLE)
| Code | Title | Credits |
|---|---|---|
| Foundation | ||
| Select four courses from the following: | 12 | |
| AI-Driven Big Data Essentials | ||
| Natural Language Processing: Theory and Practice | ||
| Interpretable Machine Learning | ||
| Applied Machine Learning | ||
| Electives | ||
| Select two courses from the following: | 6 | |
| Programming Essentials | ||
| Foundations of Applied AI | ||
| Information Technology, Ethics, and Society | ||
| Introduction to Applied Machine Learning | ||
| Project Management Concepts and Methods | ||
| Capstone Seminar | ||
| Advanced Topics in Applied Information Technology | ||
| Theories and Models in Geo-Social Data Analytics | ||
| Data Analytics in Social Media | ||
| Natural Language Processing with Deep Learning | ||
| Applied Deep Learning | ||
| Advanced Special Topics in Applied Information Technology | ||
| Master's Thesis | ||
| Total Credits | 18 | |
Online Applied Information Technology, MS Requirements
Core Courses
| Code | Title | Credits |
|---|---|---|
| Required Courses | ||
| AIT 512 | Algorithms and Data Structures Essentials | 3 |
| AIT 524 | AI-Augmented Database Management Systems | 3 |
| AIT 542 | Fundamentals of Computing Platforms | 3 |
| AIT 664 | Information: Representation, Processing and Visualization | 3 |
| Total Credits | 12 | |
Available Concentrations
- Applied Artificial Intelligence Technologies (AAIT)
- Cyber Security (CYBR)
- Data Analytics and Intelligence Methods (DAIN)
- Machine Learning Engineering (MLE)
Applied Artificial Intelligence Technologies (AAIT)
| Code | Title | Credits |
|---|---|---|
| Foundation | 12 | |
| Foundations of Applied AI | ||
| Foundations of Data Processing | ||
| Information Technology, Ethics, and Society | ||
| AI Application Development | ||
| Electives | ||
| Select two courses from the following: | 6 | |
| Programming Essentials | ||
| AI-Driven Big Data Essentials | ||
| Natural Language Processing: Theory and Practice | ||
| Total Credits | 18 | |
| Code | Title | Credits |
|---|---|---|
| Foundation | 12 | |
| Cyber Security Fundamentals | ||
| Cloud Computing Security | ||
| Secure Software Development | ||
| Network and Systems Security | ||
| Electives | ||
| Select two courses from the following: | 6 | |
| Programming Essentials | ||
| Foundations of Applied AI | ||
| Identity and Access Management | ||
| Applied Machine Learning | ||
| Total Credits | 18 | |
Data Analytics and Intelligence Methods (DAIN)
| Code | Title | Credits |
|---|---|---|
| Foundation | 12 | |
| Foundations of Data Processing | ||
| AI-Driven Big Data Essentials | ||
| Knowledge Mining from Big-Data | ||
| Intelligence Analysis Methods | ||
| Electives | ||
| Select two courses from the following: | 6 | |
| Programming Essentials | ||
| Foundations of Applied AI | ||
| Natural Language Processing: Theory and Practice | ||
| Applied Machine Learning | ||
| Total Credits | 18 | |
Machine Learning Engineering (MLE)
| Code | Title | Credits |
|---|---|---|
| Foundation | 12 | |
| AI-Driven Big Data Essentials | ||
| Natural Language Processing: Theory and Practice | ||
| Interpretable Machine Learning | ||
| Applied Machine Learning | ||
| Electives | ||
| Select two courses from the following: | 6 | |
| Programming Essentials | ||
| Foundations of Applied AI | ||
| Natural Language Processing with Deep Learning | ||
| Applied Deep Learning | ||
| Total Credits | 18 | |
- Applied Science, BAS (Cyber Security Concentration)/Applied Information Technology, Accelerated MS
- Applied Science, BAS (Data Analytics Concentration)/Applied Information Technology, Accelerated MS
- Information Technology, BS/Applied Information Technology, Accelerated MS
- Mechanical Engineering, BS/Applied Information Technology, Accelerated MS
Applied Science, BAS (Cyber Security Concentration)/Applied Information Technology, Accelerated MS
Overview
Highly-qualified undergraduates may be admitted to the combined Bachelor's/Accelerated master's degree pathway program (accelerated master's) and obtain a bachelor's degree (BAS) in Applied Science, and a Master of Science (MS) in Applied information Technology. This BAS to MS pathway is only open to students within the Cyber Security concentration of BAS.
This accelerated option is offered jointly by the undergraduate BAS program and the graduate Applied Information Technology program in the College of Engineering and Computing.
See AP.6.7 Bachelor's/Accelerated Master's Degrees for policies related to this program.
Students in an accelerated master’s degree program must fulfill all university
requirements for the master's degree. For policies governing all graduate degrees, see AP.6 Graduate Policies.
BAM Pathway Admission Requirements
Applicants to all graduate programs at George Mason University must meet the admission standards and application requirements for graduate study as specified in Graduate Admissions Policies and accelerated master's degree policies. For information specific to this accelerated master's program, see the BAS website and consult with a BAS academic advisor.
Students will be considered for admission into the BAM Pathway after completion of a minim of 60 credits, and a cumulative GPA of 3.30 or higher.
Students who are accepted into the BAM Pathway will be allowed to register for graduate level courses after successful completion of a minimum of 75 undergraduate credits and any pathway-specific course pre-requisites.
Accelerated Master's Admission Requirements
Undergraduate students already admitted to the BAM Pathway will be admitted to the intended master's program if they have met the following criteria, that will be verified:
- Submission of the BAM Transition Form by the stated deadline.
- Timely completion of the Application for Degree.
- Sufficient minimum 3.30 cumulative GPA for conferred undergraduate degree (which does not include any earned reserve graduate credits).
- All requirements as noted in AP.6.7.3 Timeline Requirements
- Completion of all BAS, Cyber Security concentration requirements and all requirements outlined in AP.5.3.2 Requirements for Bachelor's Degrees
- Completion of approved advanced standing courses and any reserve courses that have met the minimum grade requirement.
Accelerated Pathway Requirements
To maintain the integrity and quality of both the undergraduate and graduate degree programs, undergraduate students interested in taking graduate courses must choose from the following:
Advanced Standing courses: Students must complete at least 3 credits from the following list of graduate-level courses, while in undergraduate status, up to a maximum of 12 credits. Within the BAS, Cyber Security concentration these courses apply towards Technical Focus requirements.
| Code | Title | Credits |
|---|---|---|
| AIT 512 | Algorithms and Data Structures Essentials 1 | 3 |
| or AIT 655 | Project Management Concepts and Methods | |
| AIT 524 | AI-Augmented Database Management Systems | 3 |
| AIT 542 | Fundamentals of Computing Platforms | 3 |
| AIT 664 | Information: Representation, Processing and Visualization | 3 |
- 1
When selecting between AIT 512 and AIT 655, students should select the course that aligns with the Applied Information Technology, MS concentration they intend to pursue. AIT 655 applies only to the IT Management (ITMG) concentration. AIT 512 applies to all other concentrations. Students are encouraged to verify course selection with a program advisor.
Reserve credit courses: Students have the option to complete up to 6 credits of graduate-level coursework while in undergraduate status that will only count towards the graduate degree program. Since course selection is dependent upon the student's planned Applied Information Technology, MS concentration, students must consult with a program advisor to select applicable coursework.
For more detailed information on coursework and timeline requirements, see AP.6.7 Bachelor's/Accelerated Master's Degree and AP.1. Graduate Course Enrollment by Undergraduates.
Applied Science, BAS (Data Analytics Concentration)/Applied Information Technology, Accelerated MS
Overview
Highly-qualified undergraduates may be admitted to the combined Bachelor's/Accelerated master's degree pathway program (accelerated master's) and obtain a bachelor's degree (BAS) in Applied Science, and a Master of Science (MS) in Applied Information Technology. This BAS to MS pathway is only open to students within the Data Analytics concentration of BAS.
This accelerated option is offered jointly by the undergraduate BAS program and the graduate Applied Information Technology program in the College of Engineering and Computing.
See AP.6.7 Bachelor's/Accelerated Master's Degrees for policies related to this program.
Students in an accelerated master’s degree program must fulfill all university
requirements for the master's degree. For policies governing all graduate degrees, see AP.6 Graduate Policies.
BAM Pathway Admission Requirements
Applicants to all graduate programs at George Mason University must meet the admission standards and application requirements for graduate study as specified in Graduate Admissions Policies and accelerated master's degree policies. For information specific to this accelerated master's program, see the BAS website and consult with a BAS academic advisor.
Students will be considered for admission into the BAM Pathway after completion of a minim of 60 credits, and a cumulative GPA of 3.30 or higher.
Students who are accepted into the BAM Pathway will be allowed to register for graduate level courses after successful completion of a minimum of 75 undergraduate credits and any pathway-specific course pre-requisites.
Accelerated Master's Admission Requirements
Undergraduate students already admitted to the BAM Pathway will be admitted to the intended master's program if they have met the following criteria, that will be verified:
- Submission of the BAM Transition Form by the stated deadline.
- Timely completion of the Application for Degree.
- Sufficient minimum 3.30 cumulative GPA for conferred undergraduate degree (which does not include any earned reserve graduate credits).
- All requirements as noted in AP.6.7.3 Timeline Requirements
- Completion of all BAS, Data Analytics concentration requirements and all requirements outlined in AP.5.3.2 Requirements for Bachelor's Degrees
- Completion of approved advanced standing courses and any reserve courses that have met the minimum grade requirement.
Accelerated Pathway Requirements
To maintain the integrity and quality of both the undergraduate and graduate degree programs, undergraduate students interested in taking graduate courses must choose from the following:
Advanced Standing courses: Students must complete at least 3 credits from the following list of graduate-level courses, while in undergraduate status, up to a maximum of 9 credits. Within the BAS, Data Analytics concentration these courses apply towards Applied Coursework requirements.
| Code | Title | Credits |
|---|---|---|
| AIT 512 | Algorithms and Data Structures Essentials 1 | 3 |
| or AIT 580 | Foundations of Data Processing | |
| AIT 524 | AI-Augmented Database Management Systems | 3 |
| AIT 542 | Fundamentals of Computing Platforms | 3 |
| AIT 664 | Information: Representation, Processing and Visualization | 3 |
- 1
When selecting between AIT 512 and AIT 580, students should select the course that aligns with the Applied Information Technology, MS concentration they intend to pursue.
Reserve credit courses: Students have the option to complete up to 6 credits of graduate-level coursework while in undergraduate status that will only count towards the graduate degree program. Courses may be selected from the list above, or in consultation with a program advisor. As the Applied Information Technology, MS program has several concentrations with unique requirements, students must be sure to select courses not listed above only if they align with their intended Applied Information Technology, MS concentration.
For more detailed information on coursework and timeline requirements, see AP.6.7 Bachelor's/Accelerated Master's Degree and AP.1. Graduate Course Enrollment by Undergraduates.
Information Technology, BS/Applied Information Technology, Accelerated MS
Overview
Highly-qualified undergraduates may be admitted to the combined bachelor's and accelerated master's degree pathway program (accelerated master's) and obtain an Information Technology, BS and an Applied Information Technology, MS in an accelerated time-frame after satisfactory completion of a minimum of 138 credits (total number of required credits depends on the requirements of both the undergraduate and graduate programs).
See AP.6.7 Bachelor's/Accelerated Master's Degrees for policies related to this program.
Students in an accelerated master’s degree program must fulfill all university
requirements for the master's degree. For policies governing all graduate degrees, see AP.6 Graduate Policies.
BAM Pathway Admission Requirements
Applicants to all graduate programs at George Mason University must meet the admission standards and application requirements for graduate study as specified in Graduate Admissions Policies and accelerated master's degree policies.
Students will be considered for admission into the BAM Pathway after completion of a minimum of 60 credits and with an overall GPA of at least 3.30.
Students who are accepted into the BAM Pathway will be allowed to register for graduate level courses after successful completion of a minimum of 75 undergraduate credits and any pathway-specific course pre-requisites.
Accelerated Master's Admission Requirements
Undergraduate students already admitted to the BAM Pathway will be admitted to the intended master’s program, if they have met the following criteria, that will be verified:
- Submission of BAM Transition Form by stated deadline.
- Sufficient minimum 3.0 cumulative GPA for conferred undergraduate degree (which does not include any earned reserve graduate credits).
- Completion of approved advanced standing courses and any reserve graduate courses that have met the minimum grade requirement.
- Successful completion of required minimum of 120 credits needed for undergraduate degree conferral (after exclusion any satisfactory reserve graduate credits earned).
- Successfully meeting George Mason’s requirements for undergraduate degree conferral (graduation) and timely submitting the application for graduation.
Accelerated Pathway Requirements
To maintain the integrity and quality of both the undergraduate and graduate degree
programs, undergraduate students interested in taking graduate courses must choose from the following:
Advanced Standing courses: Students must complete at least 3 credits from the following list of graduate-level courses, while in undergraduate status, up to a maximum of 12 credits.
| Code | Title | Credits |
|---|---|---|
| AIT 512 | Algorithms and Data Structures Essentials (satisfies the IT 306 requirement in the BS INFT program) | 3 |
| AIT 524 | AI-Augmented Database Management Systems (satisfies the IT 314 requirement in the BS INFT program) | 3 |
| AIT 536 | Foundations of Applied AI (satisfies IT 371) | 3 |
| AIT 542 | Fundamentals of Computing Platforms (satisfies the IT 342 requirement in the BS INFT program) | 3 |
| AIT 580 | Foundations of Data Processing (satisfies the IT 374 requirement in the BS INFT program) | 3 |
| AIT 618 | Human-AI Interaction (satisfies SYST 469) | 3 |
| AIT 646 | Introduction to Applied Machine Learning (satosfies IT 416) | 3 |
| AIT 664 | Information: Representation, Processing and Visualization (satisfies IT 373 requirement in the BS INFT program) | 3 |
| AIT 670 | Cloud Computing Security (satisfies IT 481) | 3 |
| AIT 682 | Network and Systems Security (satisfies the IT 366 requirement in the BS INFT program) | 3 |
Reserve credit courses: Students may complete up to 6 credits, while in undergraduate student status, of graduate-level coursework from the list above that will only count toward the graduate degree program.
For more detailed information on coursework and timeline requirements, see AP.6.7 Bachelor's/Accelerated Master's Degree and AP.1. Graduate Course Enrollment by Undergraduates.
Mechanical Engineering, BS/Applied Information Technology, Accelerated MS
Overview
Highly-qualified undergraduates may be admitted to the bachelor's/accelerated master's program and obtain a Mechanical Engineering, BS and an Applied Information Technology, MS in an accelerated time-frame after satisfactory completion of a minimum of 139 credits.
See AP.6.7 Bachelor's/Accelerated Master's Degrees for policies related to this program.
Students in an accelerated degree program must fulfill all university requirements for the master's degree. For policies governing all graduate degrees, see AP.6 Graduate Policies.
BAM Pathway Admission Requirements
Applicants to all graduate programs at George Mason University must meet the admission standards and application requirements for graduate study as specified in Graduate Admissions Policies and Bachelor's/Accelerated Master's Degree policies.
Mechanical Engineering, BS Students will be considered for admission into the BAM Pathway after completion of a minimum of 60 credits with an overall GPA of at least 3.0.
Students who are accepted into the BAM Pathway will be allowed to register for graduate level courses after successful completion of a minimum of 75 undergraduate credits and course-specific pre-requisites.
The criteria for admission are identical to criteria for admission to the Applied Information Technology, MS program.
Accelerated Pathway Requirements
To maintain the integrity and quality of both the undergraduate and graduate degree programs, undergraduate students interested in taking graduate courses must choose from the following:
Advanced Standing Courses
Students must complete all credits that satisfy requirements for both the BS and MS programs. Up to four courses (12 credits) of approved master’s level courses taken as part of the undergraduate degree may be applied to the graduate degree.
| Code | Title | Credits |
|---|---|---|
| AIT 512 | Algorithms and Data Structures Essentials 1 | 3 |
| AIT 524 | AI-Augmented Database Management Systems | 3 |
| AIT 542 | Fundamentals of Computing Platforms | 3 |
| AIT 655 | Project Management Concepts and Methods 2 | 3 |
| AIT 664 | Information: Representation, Processing and Visualization | 3 |
- 1
This course should be selected for all concentrations except for the IT Management concentration
- 2
This course should be selected for the IT Management concentration
While still in undergraduate status, a maximum of 6 additional graduate credits may be taken as reserve graduate credit and applied to the master's program. Students are strongly encouraged to meet with a graduate advisor to select reserve graduate credits. Reserve credits must come from courses that fulfill the intended master’s degree requirements. Reserve graduate credits do not apply to the undergraduate degree.
Degree Conferral
Students must apply the semester before they expect to complete the BS requirements to have the BS degree conferred. In addition, at the beginning of the student's final undergraduate semester, students must complete a Bachelor's/Accelerated Master's Transition form. At the completion of MS requirements, a master's degree is conferred.