Program Overview
The MS in Applied Information Technology program educates IT leaders to design, implement, and manage complex systems. Students can specialize in Cyber Security, Data Analytics and Intelligence Methods, Machine Learning Engineering, or IT Management. This graduate program is offered online in an accelerated 8-week format and can be completed in approximately 2.5 years. Graduates are prepared for careers in the private and federal sectors, focusing on areas such as Cyber Security, Big Data Analytics, and Knowledge Mining.
Program Outline
Degree Overview:
The MS in Applied Information Technology is a graduate program designed for high-potential leaders in the IT field, particularly those working on IT solutions for the federal government, industry, or non-profit organizations. The program aims to graduate individuals with the competence and character to lead multidisciplinary teams in the design, justification, development, management, and sustainment of large-scale systems, from data to decision, in both the private and federal sectors. The MS in AIT offers a high-quality curriculum for students seeking careers in leading IT areas, including Cyber Security, Big Data Analytics, Knowledge Mining, Data Analytics in Social Media, and Cyber-Human Interaction.
Outline:
The MS AIT program offers three concentrations: Cyber Security, Data Analytics and Intelligence Methods, and Machine Learning Engineering. The program is available fully online, with courses offered in a condensed 8-week format, allowing students to take one course at a time. The online program is designed to be completed in approximately 2.5 years.
Core Courses:
All students are required to complete four core courses:
- AIT 512 Algorithms and Data Structures Essentials
- AIT 524 Database Management Systems
- AIT 542 Fundamentals of Computing Platforms
Concentrations:
Students must choose a concentration within the program by taking six courses from one of the following areas:
- Cyber Security (CYBR): Foundation courses include AIT 660 Cyber Security Fundamentals, AIT 670 Cloud Computing Security, AIT 681 Secure Software Development, AIT 682 Network and Systems Security, AIT 688 IoT Security, and AIT 702 Incident Handling and Penetration Testing. Electives include AIT 502 Programming Essentials, AIT 590 Topics in Applied Information Technology, AIT 602 Introduction to Research in Applied Information Technology, AIT 636 Interpretable Machine Learning, AIT 669 Advanced Information Security Risk Management, AIT 672 Identity and Access Management, AIT 687 IoT and Edge Systems, AIT 690 Advanced Topics in Applied Information Technology, AIT 699 Research Project, AIT 701 Cyber Security: Emerging Threats and Countermeasures, AIT 712 Applied Biometric Technologies, AIT 736 Applied Machine Learning, AIT 746 Applied Deep Learning, AIT 790 Advanced Special Topics in Applied Information Technology, and AIT 799 Master's Thesis. Electives include AIT 502 Programming Essentials, AIT 526 Introduction to Natural Language Processing, AIT 590 Topics in Applied Information Technology, AIT 602 Introduction to Research in Applied Information Technology, AIT 611 Rapid Information Systems Prototyping, AIT 624 Knowledge Mining from Big-Data, AIT 636 Interpretable Machine Learning, AIT 642 Interaction Design and Accessibility, AIT 684 Interactive Visualization and Data Analytics, AIT 690 Advanced Topics in Applied Information Technology, AIT 699 Research Project, AIT 711 Rapid Development of Scalable Applications, AIT 716 Advanced Human Computer Interaction, AIT 722 Theories and Models in Geo-Social Data Analytics, AIT 726 Natural Language Processing with Deep Learning, AIT 734 Advanced Web Analytics Using Semantics, AIT 736 Applied Machine Learning, AIT 746 Applied Deep Learning, AIT 790 Advanced Special Topics in Applied Information Technology, and AIT 799 Master's Thesis. Electives include AIT 502 Programming Essentials, AIT 616 Interactive Machine Learning and Artificial Intelligence, AIT 642 Interaction Design and Accessibility, AIT 690 Advanced Topics in Applied Information Technology, AIT 699 Research Project, AIT 790 Advanced Special Topics in Applied Information Technology, AIT 799 Master's Thesis, and COMP 522 Accessibility and Assistive Technologies.
- Machine Learning Engineering (MLE): Foundation courses include AIT 526 Introduction to Natural Language Processing, AIT 614 Big Data Essentials, AIT 636 Interpretable Machine Learning, and AIT 736 Applied Machine Learning.
Careers:
The program aims to prepare students for leadership roles in the IT field, particularly in areas like Cyber Security, Big Data Analytics, Knowledge Mining, Data Analytics in Social Media, and Cyber-Human Interaction. The program's focus on developing skills in design, justification, development, management, and sustainment of large-scale systems makes graduates well-suited for positions in both the private and federal sectors.
Other:
The program offers a concentration in the INFT PhD program at the doctoral level. 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 and meet with an advisor before applying to the program. Students in all concentrations may take other CEC graduate-level courses not listed above as part of their MS technical electives, subject to prior advisor approval.
