Information Systems and Emerging Technologies, M.S.
The Master of Science in Information Systems and Emerging Technologies program prepares students to design, develop, integrate, and scale intelligent, secure, and AI-driven digital systems that power modern enterprises. Rooted in applied computing and software engineering, the program emphasizes real-world application through the hands-on development of cloud-native, data-intensive architectures. Students gain deep expertise in applied artificial intelligence, intelligent automation, and emerging technologies, learning to engineer robust, human-centered systems that integrate generative AI and ethical design principles. Graduates will be equipped to transform complex data into actionable insights, deploy enterprise-grade solutions, and lead digital innovation across industries. Through applied projects and a culminating capstone experience centered on the design and implementation of real-world enterprise solutions, graduates leave with practical experience and a portfolio-ready demonstration of their capacity to drive technological advancement and organizational impact. Designed with accessibility and flexibility in mind, the program welcomes applicants from a broad range of academic and professional backgrounds.
Through applied projects and a culminating capstone experience centered on the design and implementation of real-world enterprise solutions, graduates leave with practical experience and a portfolio-ready demonstration of their capacity to drive technological advancement and organizational impact.
Along the way, you’ll learn from a network of diverse peers from around the world, merging technology with human and organizational structures as you engage in knowledge discovery, management and dissemination of industry-critical knowledge.
You can also earn a graduate certificate that complements a master’s degree, often without taking additional credits, allowing you to tailor the program to your specific interests.
As part of the School for Professional Studies, this 30-credit master's program offers data-driven professionals like you a flexible option to meet your career goals. With multiple start terms, you can begin the master's program in the fall or spring. You will join a community of academics and practitioners from a wide range of subjects and professional backgrounds, providing the opportunity to learn from a network of peers.
The 100% online program offers flexible courses in eight-week terms, making advanced education more accessible for working professionals.
Some SPS programs are also offered in on-campus versions, created so that international students can meet their visa requirements.
Faculty
As a student in the School for Professional Studies at Saint Louis University, you’ll learn from exceptional faculty who are leading experts in their fields. They bring real-world knowledge to the classroom and are dedicated to your professional success. Learn more about the SPS faculty.
Careers
SLU's Master of Science in Information Systems and Emerging Technologies can prepare you for potential jobs such as Information Systems Manager, Enterprise Architect, Cloud Solutions Architect, Emerging Technologies Strategist, IT Transformation Consultant, Digital Innovation Manager, Data & Systems Integration Specialist, Technology Product Manager, IT Governance & Risk Analyst, Solutions Engineer, Chief Technology Officer (CTO) pathway.
Tuition
| Tuition | Total Program Cost |
|---|---|
| On-Ground MS Applied AI and Decision Analytics, MS Cybersecurity, MS Information Systems and Emerging Technologies, MS Project Management, MS Technology Leadership | $42,000 |
| Tuition | Cost Per Credit |
|---|---|
| Online Graduate Degrees and Post-Baccalaureate Certificates | $810 |
Additional charges may apply. Other resources are listed below:
Scholarships and Financial Aid
For priority consideration for graduate assistantship, apply by Feb. 1.
For more information, visit the Office of Student Financial Services.
- Graduates will be able to apply program-specific knowledge to address practical problems using an ethical, evidence-based framework.
- Graduates will be able to utilize argumentation skills appropriate for a given problem or context.
- Graduates will be able to analyze business problems and implement intelligent, secure, and scalable information technology solutions that support the goals of the organization.
- Graduates will be able to lead the adoption and integration of emerging technologies to support the strategic goals of an information systems organization.
Admission Requirements
- Completed application
- Undergraduate degree (most successful applicants have an undergraduate grade point average of 3.0 or better)
- Official transcript from a degree-granting institution
- Resume or curriculum vitae
- External reference recommendations (encouraged but not required)
Upon admission, a new online student* must successfully complete a virtual meeting with their academic coach to be enrolled in first-term coursework.
- *
This is for 100% online students only. International on-campus graduate students will meet their academic coach at on-campus orientation.
Requirements for International Students
All admission policies and requirements for domestic students apply to international students, along with the following:
- Applicants must demonstrate English language proficiency. Some examples of demonstrated English language proficiency include minimum score requirements for the following standardized tests:
- Paper-based TOEFL: 550
- Internet-based TOEFL: 80
- IELTS: 6.5
- PTE: 54
• Academic records, in English translation, of students who have undertaken postsecondary studies outside the United States must include the courses taken and/or lectures attended, practical laboratory work, the maximum and minimum grades attainable, the grades earned or the results of all end-of-term examinations, and any honors or degrees received. WES and ECE transcripts are accepted.
Program Requirements
| Code | Title | Credits |
|---|---|---|
| Required SPS Graduate Courses | ||
| AA 5221 | Applied Analytics & Methods I * | 3 |
| ORLD 5050 | Ethical, Evidence-Based Decision Making | 3 |
| IS 5101 | AI-Enhanced Software Development Practice | 3 |
| Foundation Courses | ||
| IS 5102 | User-Centric Software Design and Innovation | 3 |
| IS 5103 | Scalable Software Systems for Data-Intensive Applications | 3 |
| AA 5110 | Data Infrastructure Engineering and Management | 3 |
| Electives or Post-Baccalaureate Certificate | 9 | |
Students should take an additional 3 courses, 9 credits, of the below electives or choose one of the below Post-Baccalaureate Certificates | ||
| Visualization, Feedback and Dissemination | ||
| Cloud Security | ||
| Enterprise Architecture and Systems Infrastructure | ||
| Information Systems Strategy and Management | ||
| Managing a Secure Enterprise | ||
| Advanced Software Development | ||
| Mobile and Web Application Development | ||
| Information Systems Consulting | ||
| Cloud Computing | ||
| Advanced Cloud Computing Architectures and Applications | ||
| Master's Project | 3 | |
| Masters Research Project | ||
| Total Credits | 30 | |
- †
Former computer science students may substitute CSCI 5030 Principles of Software Development (3 cr) for IS 5101 AI-Enhanced Software Development Practice (3 cr) and former health data sciences students may substitute HDS 5210 Programming for Health Data Scientists (3 cr) for IS 5101 AI-Enhanced Software Development Practice (3 cr)
- ‡
Former computer science students may substitute CSCI 5710 Databases (3 cr) for AA 5110 Data Infrastructure Engineering and Management (3 cr) and former business students may substitute ITM 6550 Big Data in Organizations (3 cr) for AA 5110 Data Infrastructure Engineering and Management (3 cr)
- §
Former business students may substitute ITM 6000 Managing Information Technology (3 cr) for IS 5000 Enterprise Architecture and Systems Infrastructure (3 cr)
- *
Former business students may substitute OPM 5020 Applied Business Statistics (3 cr) for AA 5221 Applied Analytics & Methods I (3 cr)
Continuation Standards
Students must maintain a cumulative grade point average (GPA) of 3.00 in all graduate/professional courses.
This roadmap is just one example of a semester-by-semester plan of study for this program. There are other plans students can and do take. The plan of study for each particular student is established in consultation with each student’s academic advisor; this roadmap does not replace academic advising appointments.
Roadmap notes:
- This Roadmap assumes full-time enrollment unless otherwise noted.
- Courses/Milestones marked with an “!” are critical and must be completed in the semester listed in the Roadmap to ensure a timely graduation.
- Course availability and sequencing are subject to change.
Students are recommended to take required courses before electives.
Fall Entry
| Year One | ||
|---|---|---|
| Fall | Credits | |
| Fall 1 | ||
| AA 5221 | Applied Analytics & Methods I | 3 |
| Fall 2 | ||
| ORLD 5050 | Ethical, Evidence-Based Decision Making | 3 |
| Credits | 6 | |
| Spring | ||
| Spring 1 | ||
| IS 5101 | AI-Enhanced Software Development Practice | 3 |
| Spring 2 | ||
| IS 5102 | User-Centric Software Design and Innovation | 3 |
| IS 5103 | Scalable Software Systems for Data-Intensive Applications | 3 |
| Credits | 9 | |
| Summer | ||
| Elective | 3 | |
| Credits | 3 | |
| Year Two | ||
| Fall | ||
| Fall 1 | ||
| Elective | 3 | |
| Fall 2 | ||
| Elective | 3 | |
| Credits | 6 | |
| Spring | ||
| IS 5960 | Masters Research Project | 3 |
| Spring 1 | ||
| AA 5110 | Data Infrastructure Engineering and Management | 3 |
| Credits | 6 | |
| Total Credits | 30 | |
Spring Entry
| Year One | ||
|---|---|---|
| Spring | Credits | |
| Spring 1 | ||
| IS 5101 | AI-Enhanced Software Development Practice | 3 |
| Spring 2 | ||
| IS 5102 | User-Centric Software Design and Innovation | 3 |
| IS 5103 | Scalable Software Systems for Data-Intensive Applications | 3 |
| Credits | 9 | |
| Summer | ||
| Elective | 3 | |
| Credits | 3 | |
| Fall | ||
| Fall 1 | ||
| AA 5221 | Applied Analytics & Methods I | 3 |
| Fall 2 | ||
| ORLD 5050 | Ethical, Evidence-Based Decision Making | 3 |
| Credits | 6 | |
| Year Two | ||
| Spring | ||
| Spring 1 | ||
| Elective | 3 | |
| Spring 2 | ||
| Elective | 3 | |
| Credits | 6 | |
| Summer | ||
| IS 5960 | Masters Research Project | 3 |
| Credits | 3 | |
| Fall | ||
| AA 5110 | Data Infrastructure Engineering and Management | 3 |
| Credits | 3 | |
| Total Credits | 30 | |
For additional admission questions, please call 314-977-2330 or email sps@slu.edu.
