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 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.
Core Courses
| Code | Title | Credits |
|---|---|---|
| Required Core Courses | 12 | |
| For students in all concentrations except the IT Management concentration: | ||
| Algorithms and Data Structures Essentials | ||
| Database Management Systems | ||
| Fundamentals of Computing Platforms | ||
| Information: Representation, Processing and Visualization | ||
| For students in the IT Management concentration: | ||
| Database Management Systems | ||
| Fundamentals of Computing Platforms | ||
| Project Management Concepts and Methods | ||
| Information: Representation, Processing and Visualization | ||
| Total Credits | 12 | |
Concentrations
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 | ||
| AI: Ethics, Policy, and Society | ||
| Foundations of Data Processing | ||
| 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 | ||
| AI and Cybersecurity | ||
| Advanced Topics in Applied Information Technology | ||
| Research Project | ||
| Natural Language Processing with Deep 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 | ||
| Topics in Applied Information Technology | ||
| Introduction to Research in Applied Information Technology | ||
| Information Technology, Ethics, and Society | ||
| Interpretable Machine Learning | ||
| Identity and Access Management | ||
| 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 | ||
| 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 | ||
| Interactive Visualization and Data Analytics | ||
| 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 | ||
| Information Technology, Ethics, and Society | ||
| Interactive Machine Learning and Artificial Intelligence | ||
| Human-AI Interaction | ||
| Interaction Design and Accessibility | ||
| 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 | ||
| Metadata Analytics for Big Data (Select two courses from the following:) | ||
| 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 | ||
| Information Technology, Ethics, and Society | ||
| 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 | |
- 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 students in the Applied Science, BAS, Cyber Security Concentration have the option of obtaining an accelerated Applied Information Technology, MS.
For more detailed information, see AP.6.7 Bachelor's/Accelerated Master's Degrees. For policies governing all graduate degrees, see AP.6 Graduate Policies.
Admission Requirements
Students in the Applied Science, BAS, Cyber Security Concentration program may apply to this option if they have earned 60 undergraduate credits with an overall GPA of at least 3.30. They may begin taking graduate-level courses once they have earned 75 undergraduate credits. Criteria for admission are identical to criteria for admission to the Applied Information Technology, MS program.
Accelerated Option Requirements
Students must complete all credits that satisfy requirements for the BAS and MS programs, with up to 12 credits overlapping from the following courses:
| Code | Title | Credits |
|---|---|---|
| AIT 512 | Algorithms and Data Structures Essentials | 3 |
| or AIT 580 | Foundations of Data Processing | |
| AIT 524 | Database Management Systems | 3 |
| AIT 542 | Fundamentals of Computing Platforms | 3 |
| AIT 660 | Cyber Security Fundamentals 1 | 3 |
| AIT 664 | Information: Representation, Processing and Visualization | 3 |
- 1
This course is only applicable to the CYBR and ITMG concentrations in the MSAIT. Students planning to pursue CBHS or DAIN should select a different course.
Note: When selecting between AIT 512 and AIT 580, students should select the course that aligns with the MSAIT concentration they intend to pursue.
Degree Conferral
Students must apply the semester before they expect to complete the BAS requirements to have the BAS 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 that is submitted to the Office of the University Registrar and the VSE Graduate Admissions Office. At the completion of MS requirements, a master’s degree is conferred.
Applied Science, BAS (Data Analytics Concentration)/Applied Information Technology, Accelerated MS
Overview
Highly-qualified students in the Applied Science, BAS, Data Analytics Concentration have the option of obtaining an accelerated Applied Information Technology, MS.
For more detailed information, see AP.6.7 Bachelor's/Accelerated Master's Degrees. For policies governing all graduate degrees, see AP.6 Graduate Policies.
Admission Requirements
Students in the Applied Science, BAS Data Analytics concentration may apply to this option if they have earned 60 undergraduate credits with an overall GPA of at least 3.30. Students may begin taking the master's level courses once they have earned 75 undergraduate credits.
Accelerated Option Requirements
Students must complete all credits that satisfy requirements for the BAS and MS programs. Students may select up to 12 credits to overlap from the following options. Students should consult with both the BAS and MSAIT advisors.
| Code | Title | Credits |
|---|---|---|
| AIT 512 | Algorithms and Data Structures Essentials 1 | 3 |
| or AIT 580 | Foundations of Data Processing | |
| AIT 524 | 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 MSAIT concentration they intend to pursue.
Information Technology, BS/Applied Information Technology, Accelerated MS
Overview
Highly-qualified students in the Information Technology, BS have the option of obtaining an accelerated Applied Information Technology, MS.
For more detailed information, see AP.6.7 Bachelor's/Accelerated Master's Degrees. For policies governing all graduate degrees, see AP.6 Graduate Policies.
Admission Requirements
Students in the Information Technology, BS program may apply to this option if they have earned 60 undergraduate credits and take graduate level courses after completion of 75 credits with an overall GPA of at least 3.30. Criteria for admission are identical to criteria for admission to the Applied Information Technology, MS program.
Accelerated Option Requirements
Students must complete all credits that satisfy requirements for the BS and MS programs, with a minimum of 3 credits (maximum 12 credits) overlapping from the following courses:
| Code | Title | Credits |
|---|---|---|
| AIT 512 | Algorithms and Data Structures Essentials (satisfies the IT 306 requirement in the BS INFT program) | 3 |
| AIT 524 | Database Management Systems (satisfies the IT 314 requirement in the BS INFT program) | 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 322 requirement in the BS INFT program) | 3 |
| AIT 664 | Information: Representation, Processing and Visualization (satisfies IT 373 requirement in the BS INFT program) | 3 |
| AIT 682 | Network and Systems Security (satisfies the IT 366 requirement in the BS INFT program) | 3 |
Students also have the option to take up to 6 additional credits of graduate coursework on reserve, which can be used for the MS degree only. Reserve credits must come from courses that fulfill the intended master’s degree requirements.
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.
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 | 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.