FRANKLIN UNIVERSITY
College of Arts, Sciences & Technology · Information Technology
M.S. in Information Technology
Fall 2026
Fall 2026
FRANKLIN UNIVERSITY
College of Arts, Sciences & Technology · Information Technology
One shared core makes you fluent across the stack — data, security, development, infrastructure, and strategy. One specialization, chosen from eight paths, makes you deep in the direction your career is heading.
The Master of Science in Information Technology builds the theoretical and practical technology-and-strategy skills of a technology manager or leader. A strong grounding in the fundamentals — networks, databases, servers, cloud, security — is only the start. As technology moves from the server room into the board room, communication, presentation, and analysis matter just as much. Every graduate leaves able to direct advanced analysis toward effective IT strategy in the domain they've chosen.
Databases, security, web development, infrastructure, project management, and strategy. Everyone builds the same foundation.
Transcript-visible depth, aimed at the work you want to do next — from cybersecurity to AI leadership.
IT Strategy & Policy. You argue IT as competitive advantage and lead a cross-disciplinary initiative, your specialization included.
Seven commitments (ITECM1–7), each anchored in a required course.
Develop advanced database systems.
Evaluate organizational security posture against the breadth of the InfoSec body of knowledge.
Develop and deploy modern web applications using current tools and technologies.
Apply standard project management best practices in an IT context.
Apply best practices for advanced infrastructure, networks, cloud, systems, and services.
Analyze IT initiatives to determine competitive parity or advantage.
Develop IT strategy in cross-disciplinary domains, proven in the capstone, specialization included.
Six courses, twelve weeks each. Databases through strategy, the full stack every IT leader needs before choosing a direction.
| Course | Title | Length | Credits |
|---|---|---|---|
| ITEC 640 | Project Management | 12 weeks | 4 |
| ITEC 660 | Web Development and Deployment | 12 weeks | 4 |
| ITEC 670 | Network, Cloud and Systems Management | 12 weeks | 4 |
| ITEC 690 | IT Strategy and Policy | 12 weeks | 4 |
| DATA 630 | Applied Database Management | 12 weeks | 4 |
| CYSC 610 | Information Assurance | 12 weeks | 4 |
Three of the eight are entirely six-week, Cybersecurity Governance, IT Management, and AI Leadership for Professionals. Cybersecurity Engineering mixes lengths. The rest run twelve weeks.
Open any path for its full course list, where it leads, and who it fits.
Policy, ethics, and risk — lead the program that protects the organization.
All 6-weekSemi-technical · three 6-week courses · shares CYSC 630 with Cybersecurity Engineering.
IT risk / GRC analyst · Information security manager · Security program & policy manager · Compliance / audit lead · Information security officer → CISO track
Security programs stall when someone can name a risk but cannot price it, prioritize it, or get the fix funded. This path is built around that transition.
You want to own security at the program level — policy, controls, metrics, and the board conversation — more than the hands-on defense.
Advanced network security and ethical hacking — build and break, defensively.
Mixed lengthTechnical · one 6-week course then two 12-week · shares CYSC 630 with Cybersecurity Governance.
Security engineer · Network security analyst · Penetration tester · SOC / incident response lead · Security architect
The hands-on track — you assess a network, defend it, and test it under authorization, rather than only describing the risk.
You want to work directly with the systems — hardening, monitoring, and authorized offensive testing.
MBA-adjacent leadership fluency for technology managers.
All 6-weekNon-technical · three 6-week courses · drawn from the MBA core.
IT manager → director · Technology operations lead · IT business partner · Portfolio / program leadership · CIO / senior leadership track
Past a certain level, advancement depends on reading a business environment and holding your own with executives — not more technical depth.
Your next move is running people and a technology function, and you want business fluency without leaving IT for a full MBA.
Lead AI adoption — no coding required. AI701 plus two of three courses.
All 6-weekNon-technical, no coding · AI 701 required, then choose two of AI 702–704 · courses also open to other master's programs.
AI product owner / program lead · AI governance or risk lead · Automation / workflow lead · Internal AI adoption advisor · AI governance committee voice
Many of these roles are still taking shape; the path builds the governance and adoption judgment they call for. Deliberately cross-sector.
You will decide how your organization adopts AI — policy, rollout, and oversight — and do not need to build the models yourself.
Turn data into decisions people act on.
12-weekSemi-technical · three 12-week courses · shares MATH 601 with Artificial Intelligence.
Business intelligence analyst / BI lead · Analytics manager · Decision-support / reporting analyst · Data product owner · Analytics-focused business analyst
Organizations are not short of data or dashboards — they are short of people who can tell whether an answer is trustworthy and make a decision-maker act on it.
You want to own the analysis behind decisions — statistics, visualization, and data mining — without going all the way to machine-learning engineering.
Applied machine learning plus the ethics and safety questions it raises.
12-weekTechnical · three 12-week courses · hands-on ML work in Python · shares MATH 601 with Data Analytics.
Applied AI / ML analyst · AI-focused analytics engineer · Model risk / evaluation analyst · Applied data scientist
The technical AI path — statistical grounding, real ML work in Python, and the ethics and safety questions that come with shipping it.
You want to build and evaluate models yourself, and you are comfortable with statistics and Python.
Bring a product to market — analysis, process, and go-to-market leadership.
12-weekSemi-technical · three 12-week courses.
Technical product manager · Product owner · Business systems analyst · Program manager · Applications lead
Someone has to stand between the people who build and the people who pay, decide what is worth making, and answer for whether it mattered. That is the job.
You want to own a technology product end to end — discovery, delivery, and growth — from the business side of engineering.
Build a custom 12-credit focus from approved graduate electives, with advisor sign-off.
Advisor-approvedLength varies with the courses chosen · your ITEC 690 capstone is scoped to the domain you define.
Whatever the individualized plan is built toward — the release valve for interdisciplinary or niche goals the seven named paths do not cover.
Same assessment as every other path: applied IT strategy in a chosen domain, proven in the capstone.
Your goal crosses two of the named paths, or targets a specific industry problem none of them center on.
The 24-credit core is unchanged. The degree is still 36 credits, still the same M.S. credential, and length and financial aid are unaffected. What changed is the 12-credit choice that follows the core: the old “Focus Area” list became seven named specializations plus a Flexible Track — each one on the transcript, each built around the work you want to do next.
Filter by what matters to you, or read the whole grid. Your specialization is a within-program choice you declare after the core, with advisor sign-off — switching early is easy.
| Specialization | Adds depth in | Technical level | Pacing | Points toward |
|---|---|---|---|---|
| Cybersecurity Engineering | Risk assessment, network defense, authorized offensive testing | Technical | Mixed (6 + 12 wk) | Security engineer, SOC lead, penetration tester, security architect |
| Cybersecurity Governance | Asset valuation, information risk, policy, controls, privacy & compliance | Semi-technical | All 6-week | GRC analyst, security program manager, compliance lead, CISO track |
| Data Analytics | Statistics → visualization & storytelling → data mining | Semi-technical | All 12-week | BI analyst, analytics manager, decision-support lead, data product owner |
| IT Management | MBA core — executive communication, business environment, leadership | Non-technical | All 6-week | IT manager → director, IT business partner, CIO track |
| Artificial Intelligence | Statistical foundations → applied ML in Python → AI ethics & safety | Technical | All 12-week | Applied AI/ML analyst, AI-focused analytics engineer, model risk analyst |
| Tech Product Management | Enterprise information systems → business/process/systems analysis → product strategy | Semi-technical | All 12-week | Technical product manager, product owner, business systems analyst, program manager |
| AI Leadership for Professionals | AI leadership foundations → governance & risk → AI-native org / agentic automation | Non-technical, no coding | All 6-week | AI program lead, AI governance/risk lead, automation lead, adoption advisor |
| Flexible Track | A custom 12-credit focus from approved 600–699 graduate courses | You decide | Varies | Whatever the individualized plan is built toward, with advisor sign-off |
Every specialization is 12 credits and every path totals 36.
Already running networks, systems, or a help desk — ready to move from keeping technology alive to deciding what the organization should do with it.
Deep in one area — development, data, security — and needs the cross-functional strategy and leadership vocabulary to lead beyond it.
Broad IT background, and wants one area of documented depth to point to. A named specialization, on the transcript, is that.
Wants to carry IT leadership into a specific arena — AI adoption, a regulated industry, product — where knowing the sector matters as much as knowing the technology.
Most students come in already doing IT work and pursue the degree to move from carrying out technology decisions to making them. The core builds the leadership breadth every graduate shares; the specialization builds depth in a specific direction — and because it is on the transcript and scoped into the capstone, that depth is documented, not just described.
Cybersecurity Engineering The through-line: this is the hands-on track — you assess a network, defend it, and test it under authorization, rather than only describing the risk.
Cybersecurity Governance The through-line: security programs stall when someone can name a risk but cannot price it, prioritize it, or get the fix funded. This path is built around that transition.
Data Analytics The through-line: organizations are not short of data or dashboards — they are short of people who can tell whether an answer is trustworthy and make a decision-maker act on it.
IT Management The through-line: past a certain level, advancement depends on reading a business environment and holding your own with executives — not more technical depth. This is MBA coursework aimed at technology leaders.
Artificial Intelligence The through-line: this is the technical AI path — statistical grounding, real ML work in Python, and the ethics and safety questions that come with shipping it.
Tech Product Management The through-line: someone has to stand between the people who build and the people who pay, decide what is worth making, and answer for whether it mattered. That is the job — with the accountability made explicit.
AI Leadership for Professionals The through-line: many of these roles are still taking shape; the path builds the governance and adoption judgment they call for. Deliberately cross-sector, and no coding required.
Some. The M.S. in Information Technology is the hands-on technology-leadership degree, so it carries co-requisites you must pass with a C or better: one programming course (COMP 501, ITEC 136, or COMP 111) and a networks-and-systems requirement (ITEC 504, or an approved combination). The core includes web development and deployment, cloud and systems management, and information assurance — real technical work, though modern AI-assisted tools are part of how it is taught. Two specializations, IT Management and AI Leadership for Professionals, require no coding at all.
100% online, 36 credit hours, in as few as 16 months. Three specializations run entirely in 6-week courses (Cybersecurity Governance, IT Management, AI Leadership); the rest are mostly 12-week.
No. Still 36 credits, still the same M.S. credential, no change to length or financial aid. The 24-credit core is unchanged. Only the 12-credit choice after the core was restructured.
The “Focus Area” list became seven named specializations plus a Flexible Track. Learning Technology, IT Leadership (PSYC-based), and Healthcare were retired; Cybersecurity was split into Engineering and Governance; Data Analytics and IT Management were recomposed; and Artificial Intelligence, AI Leadership for Professionals, and Tech Product Management were added. See New for Fall 2026.
Yes. You are admitted to one M.S. in Information Technology and declare your specialization after the core, as a within-program choice. Switching early is straightforward; confirm the mechanics with your advisor.
Yes — every specialization appears on your transcript. And the ITEC 690 capstone is scoped to your specialization domain and assessed there (against program outcome ITECM7), so the depth is documented at the program level, not just listed.
They are intentionally separate. Artificial Intelligence is the technical path — statistics, applied machine learning in Python, AI ethics. AI Leadership for Professionals is for leading AI adoption without coding — governance, responsible adoption, and agentic-automation leadership. Different students, different roles.
A custom 12-credit specialization built with your advisor from approved 600–699 graduate courses (CYSC, COMP, CLOUD, BUSA, DATA, MIS, MATH). It is the release valve for interdisciplinary or niche goals the seven named paths do not cover; your capstone is scoped to your self-defined domain.