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Master of Science inInformation Science

Program summary

The online information science master’s degree program can prepare you to face evolving IT challenges, including integration, security, analyzing data, developing state-of-the-art IT applications, and managing IT staff and projects to ensure business continuity.

Application deadline

Apply by April 15 to start May 13

Credits and costs

33 Credits$1,017 per credit

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Our graduate IT programs are highly ranked by U.S. News & World Report.

Earn a Penn State Information Science Master's Degree — 100% online

The 33-credit Master of Science in Information Science offered online through Penn State World Campus presents a well-rounded and holistic computing and information technology (IT) curriculum.

The program is designed for mid-level information technology professionals who want to improve their skills, increase their knowledge, and move into a leadership or management position within the IT field. As a student in this program, you can gain a competitive edge in your field and deepen your understanding of IT by:

  • gaining expertise in business processes and the seamless integration of technology across multiple business functions
  • learning to model and engineer software and information systems that bolster an organization's operational efficiency
  • grasping both established and emerging theories and principles to drive continual improvement in IT systems
  • honing the ability to implement and oversee information systems and networks, while protecting sensitive information assets
  • acquiring data analytics, mining, and visualization skills along with machine learning skills so you can lead teams and projects, communicate effectively, and make informed decisions based on sound legal and ethical principles

Your Online Information Science Courses

The courses in this program emphasize data-driven IT and will help you acquire the knowledge and skills needed to meet evolving challenges of integration, security, and business continuity. To earn your degree, you will be required to complete a total of 33 credits. You can select core and elective courses to fit your interests and professional goals. Course subjects include:

  • information system architecture
  • big data and emerging information technologies
  • cybersecurity and information protection
  • enterprise solution design
  • enterprise digital transformation

You must also successfully complete INSC 594, a 3-credit integrative research topics course, which includes a master's scholarly paper.

Why Pursue a Penn State Degree Online?

Penn State World Campus offers a flexible, online platform that allows you to pursue a world-class education while you continue to gain valuable work experience. You will receive the same education as a resident Penn State student, and your courses will be taught by the same graduate faculty who are active in research and experts in their fields.

Information for Military and Veterans

Are you a member of the military, a veteran, or a military spouse? Please visit our military website for additional information regarding financial aid, transfer credits, and application instructions.

Courses

As a student in this program, you will have the opportunity to master emerging theories and technologies in enterprise information systems. You'll also research and study solutions to transform enterprise systems to meet the needs of ever-changing business operations.

To graduate, you must successfully complete a total of 33 course credits at the 400-, 500-, or 800-level, including:

  • at least 18 credits of required core courses
  • at least 12 credits of approved electives
  • three credits of INSC 594, an integrative research topics course, which includes a master's scholarly paper

Required Courses (18 credits)

  • 3
    credits

    Design and development of business processes that align business objectives with Information Technology (IT) systems.

  • 3
    credits

    This course will explore various emerging theories and technologies in information science, including at least cloud computing, mobile application, Internet of things, blockchain, machine learning, and artificial intelligence.

  • 3
    credits

    A web-centric look at the latest techniques and practices in computer security as they apply to the internet.

    • Prerequisite

      CSE 453 or IST 815

  • 3
    credits

    This course will investigate the evolution of information systems architecture.

  • 3
    credits

    Practical benefits of data mining will be presented; data warehousing, data cubes, and underlying algorithms used by data mining software.

    • Prerequisite

      INSC 521, or approval of instructor or department

  • 3
    credits

    Advances in design, development, and deployment of control and management software for enterprise and production information systems.

Electives (select 12 credits)

  • 3
    credits

    Examination of large-scale data storage technologies including NoSQL database systems for loosely-structured data, and warehouses for dimensional data.

  • 3
    credits

    This course will explore the development of analytics systems and the application of best practices and established software design principles using the Python programming language and its several toolkits.

    • Prerequisite

      STAT 500

  • 3
    credits

    This course provides a foundation in the principles, concepts, techniques, and tools for visualizing large data sets.

  • 3
    credits

    Application and interpretation of analytics for real-life decision making.

    • Prerequisite

      STAT 500

  • 3
    credits

    The course examines business intelligence in the era of big data. Emphasis is on the successful implementation of big data in large and small corporations that deliver extraordinary results.

  • 3
    credits

    Survey course on the key topics in predictive analytics. Students will learn methods associated with data analytics techniques and apply them to real examples using the R statistical system.

    • Prerequisite

      STAT 500 or equivalent

  • 3
    credits

    The requirements capture, design, and development of relational database applications; analysis of business requirements and development of appropriate database systems.

  • 3
    credits

    This course will employ several methods and measures from the area of social network analysis to study the interrelatedness of cyber-social and cyber-technical aspects of an organization or the society as a whole to detect and capture the dynamic patterns of group membership and structure. This type of analysis can be useful in uncovering potential threats and attacks and predicting criminal behavior and evolution of criminal networks.

  • 3
    credits

    Descriptive statistics, hypothesis testing, power, estimation, confidence intervals, regression, one- and 2-way ANOVA, Chi-square tests, diagnostics.

Culminating Experience (3 credits)

  • 3
    credits

    Supervised student activities on research projects identified on an individual or small-group basis, leading to M.S. scholarly papers.

Costs and Financial Aid

Graduate Tuition

Graduate tuition is calculated based on the number of credits for which you register. Tuition is due shortly after each semester begins and rates are assessed every semester of enrollment.

2023–24 Academic Year Rates

Tuition rates for the fall 2023, spring 2024, and summer 2024 semesters.

How many credits do you plan to take per semester?Cost
11 or fewer$1,017 per credit
12 or more$12,203 per semester

2024–25 Academic Year Rates

Tuition rates for the fall 2024, spring 2025, and summer 2025 semesters.

How many credits do you plan to take per semester?Cost
11 or fewer$1,027 per credit
12 or more$12,325 per semester

Financial Aid and Military Benefits

Some students may qualify for financial aid. Take the time to research financial aid, scholarships, and payment options as you prepare to apply. Military service members, veterans, and their spouses or dependents should explore these potential military education benefits and financial aid opportunities, as well.

How to Apply

Deadlines and Important Dates

Your degree application, including receipt of all transcripts, must be received by the following deadlines to be considered complete.

  • Summer DeadlineApply by April 15 to start May 13
  • Fall DeadlineApply by July 15 to start August 26
  • Spring DeadlineApply by November 15 to start January 13

Admissions Help

Thank you for your interest in applying to this program. Contact an admissions counselor to discuss your educational goals, financial aid options, and application deadlines. 

For admission to the Graduate School, you must hold either (1) a baccalaureate degree from a regionally accredited U.S. institution or (2) a tertiary (postsecondary) degree that is deemed comparable to a four-year bachelor's degree from a regionally accredited U.S. institution. This degree must be from an officially recognized degree-granting institution in the country in which it operates.

Prerequisites

Students intending to earn the MSIS should hold a bachelor's degree in information systems, information science, or other quantitative, scientific, or business discipline. Those with experience in information technology will also be considered for admission to the program. Students should have earned at least a 3.00 junior/senior average (on a 4.00 scale) in their baccalaureate program.

Although not required, scores from the Graduate Record Examinations (GRE) or the Graduate Management Admissions Test (GMAT) will be considered by the admissions committee if submitted. If the admissions committee determines an area of weakness or insufficient baccalaureate preparation, the student may be required to take one pre-program requirement course (IST 140). The pre-program requirements do not count toward the 33-credit program total.

Applications are submitted electronically and include a nonrefundable application fee. You will need to upload the following items as part of your application:

What You Need

Official transcripts from each institution attended, regardless of the number of credits or semesters completed. Transcripts not in English must be accompanied by a certified translation. Penn State alumni do not need to request transcripts for credits earned at Penn State, but must list Penn State as part of your academic history. If you are admitted, you will be asked to send an additional official transcript. You will receive instructions at that time.

GPA and Test Scores — All applicants are expected to have earned a junior/senior grade-point average of 3.0 or higher.

GRE or GMAT scores are NOT required for admission but will be considered if provided.

English Proficiency — The language of instruction at Penn State is English. With some exceptions, international applicants must take and submit scores for the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS). Minimum test scores and exceptions are found in the English Proficiency section on the Graduate School's "Requirements for Graduate Admission" page. Visit the TOEFL website for testing information. Penn State's institutional code is 2660.

Reference (1) — You will need to initiate the process through the online application by entering the name, email address, and mailing address of one (1) reference. Upon submission of your application, an email will be sent to your reference requesting they complete a brief online recommendation regarding your commitment to success in an online program. Please inform your reference that they must submit the form in order for your application to be complete.  

Program-Specific Questions/Materials

Résumé — Upload your résumé to the online application.

Statement of Purpose — Provide a one-page written statement of intent, highlighting academic background, work experience, skills, strengths, academic interests, and professional goals.

You can begin your online application at any time. Your progress within the online application system will be saved as you go, allowing you to return at any point as you gather additional information and required materials.

Start Your Application

Begin the graduate school application

  • Choose Enrollment Type: "Degree Admission"
  • Choose "WORLD CAMPUS" as the campus

Checking Your Status

You can check the status of your application by using the same login information established for the online application form. 

Technical Requirements 

Given the scale of data and computing used in this program and the continuous advances in tools and platforms used in information science, students are urged to check individual course technical requirements vigilantly. At a minimum, students will need a PC or laptop that runs Windows 10 or higher with 8GB of RAM and 250GB of free space on the hard drive. Mac OS machines are not compatible for most courses in the program and are not recommended.

What to Expect

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Ready to take the next step toward your Penn State master's degree?

Apply by April 15 to start May 13. How to Apply 

Start or Advance Your Career

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You can use the knowledge gained from this program and the support of Penn State career resources to pursue careers in a variety of fields, depending on your goals.


Job Titles Related to This Degree

This degree can prepare you for any number of professional roles in business, healthcare, finance, nonprofits, military, and government. The following roles are often held by people with this type of degree:
  • Application Development Director
  • Computer Systems Analyst
  • Computing Services Director
  • Information Technology Director (IT Director)
  • IT Project Manager (Information Technology Project Manager)
  • Solutions Architect

Employment Outlook for Occupational Fields Related to This Degree

Estimates of employment growth and total employment are provided by the U.S. Bureau of Labor Statistics and are subject to change. While these occupations are often pursued by graduates with this degree, individual outcomes may vary depending on a variety of factors. Penn State World Campus cannot guarantee employment in a given occupation.

Computer and Information Systems Managers

15.4%
employment growth (10 years)
533,220
total employment

Computer Systems Analysts

9.6%
employment growth (10 years)
505,210
total employment

Career Services to Set You Up for Success

Student having a virtual meeting on a laptop with a career counselor

From the day you're accepted as a student, you can access resources and tools provided by Penn State World Campus Career Services to further your career. These resources are beneficial whether you're searching for a job or advancing in an established career.

  • Opportunities to connect with employers
  • Career counselor/coach support
  • Occupation and salary information
  • Internships
  • Graduate school resources 

Contact Us

To learn more about the Master of Science in Information Science, offered in partnership with the Penn State Great Valley School of Graduate Professional Studies, please contact:

For questions about the program:
Robin G. Qiu, PhD, Professor of Information Science
Email: [email protected]

For general questions about Penn State World Campus:
World Campus Admissions Counselors
Phone: 814-863-5386
Email: [email protected]

Faculty

  • Youakim Badr

    • Degree
      H.D.R., University of Lyon
    • Degree
      Ph.D., Computer Science, National Institute of Applied Sciences (INSA-Lyon)
    • Degree
      M.S., Mathematical Modeling and Scientific Software Engineering, Francophone University Agency
    • Degree
      M.S., Computer Science, Lebanese University
    • Degree
      B.S., Computer Science, Lebanese University

    Dr. Youakim Badr, professor of data analytics, teaches courses in analytics programming, analytics systems design, data mining and predictive analytics. His research interests include smart service computing, IoT, information security, big data, machine learning, and built-in analytics. Dr. Badr is a professional member of IEEE, a lifetime member of ACM, and associate member of the ACM special interest group on knowledge discovery and data mining (SIGKDD).

  • Adrian S. Barb

    • Degree
      Ph.D., Computer Science, University of Missouri
    • Degree
      MBA, Finance and Management Information Systems, University of Missouri
    • Degree
      B.S., Industrial Engineering, University of Bucharest

    Dr. Adrian S. Barb, associate professor of information science, teaches databases, data mining, and big data courses. He has worked as a database programmer analyst as well as a web developer at University of Missouri. His research interests include data mining, knowledge discovery in databases, knowledge representation and exchange in content-based retrieval systems, semantic modeling and retrieval, conceptual change, ontology integration, and expert-in-the-loop knowledge generation and exchange.

  • Joanna F. DeFranco

    • Degree
      Ph.D., Computer and Information Science, New Jersey Institute of Technology
    • Degree
      M.S., Computer Engineering, Villanova University
    • Degree
      B.S., Electrical Engineering and Math, Penn State

    Dr. Joanna F. DeFranco is an assistant professor of software engineering. She has worked as an electronics engineer for the Navy and as a software engineer at Motorola. Her research interests include software engineering teams, effective teamwork, Internet of Things, and software-intensive critical systems.

  • Phillip A. Laplante

    • Degree
      Ph.D., Computer Science, Stevens Institute of Technology
    • Degree
      M.B.A., University of Colorado
    • Degree
      M.Eng., Electrical Engineering, Stevens Institute of Technology
    • Degree
      B.S., Systems Planning and Management, Stevens Institute of Technology

    Dr. Phillip A. Laplante is a professor of software and systems engineering. He has an extensive list of publications and deep practical experience in requirements engineering, development, testing, and project management for a variety of complex systems, including safety critical and embedded ones. He is widely recognized for work in real-time systems, real-time imaging, and applications in the Internet of Things. He is also a pioneer in licensing of software engineers, having led the development and acceptance of the first licensure exam for software engineers in the United States.

  • Colin Neill

    • Degree
      Ph.D., Software and Systems Engineering, University of Wales Swansea
    • Degree
      M.Sc., Communications Systems, University of Wales Swansea
    • Degree
      B.Eng., Electrical Engineering, University of Wales Swansea

    Dr. Colin Neill is a professor of software engineering and systems engineering. He teaches many courses in software and systems engineering and project management. He is the author of more than 80 articles on the development and evolution of complex software and systems and their management and governance. Dr. Neill is a senior member of the IEEE and a member of INCOSE, and he serves as associate editor-in-chief of Innovations in Systems and Software Engineering.

  • Robin G. Qiu

    • Degree
      Ph.D., Industrial Engineering, Penn State
    • Degree
      Ph.D., (Minor), Computer Science, Penn State
    • Degree
      M.S., Numerical Control, Beijing Institute of Technology, China
    • Degree
      B.S., Mechanical Engineering, Beijing Institute of Technology, China

    Dr. Robin G. Qiu is a professor of information science at Penn State. He teaches courses on data analytics, information science, software engineering, and cyber security. Dr. Qiu's research includes smart service systems, IoT, big data, data/business analytics, information systems and integration, supply chain and industrial systems, and analytics. He served as the editor-in-chief of INFORMS Service Science. He is an associate editor of IEEE Transactions on Systems, Man, and Cybernetics and IEEE Transactions on Industrial Informatics, and has more than 160 publications.

  • Dusan Ramljak

    • Degree
      Ph.D., Computer and Information Sciences, CST, Temple University
    • Degree
      M.Sc. and B.Sc., Electrical Engineering - Systems Control, University of Belgrade, Serbia

    Dr. Dusan Ramljak, assistant teaching professor of information science, teaches courses on information science, data science, storage systems, and emerging technologies. He has been applying data science on storage systems in NSF IUCRC projects with HPE, Dell, Huawei, and other companies and has more than 20 years of system administration experience facilitating business and research in the U.S., Portugal, and Serbia. His research interests include solving challenging storage systems, provenance, and caching problems, and developing and integrating distributed and parallel data mining and statistical learning technology for an efficient knowledge discovery at large sequence and temporal databases.

  • Raghvinder S. Sangwan

    • Degree
      Ph.D., Computer and Information Sciences, Temple University
    • Degree
      M.S., Computer Science, West Chester University
    • Degree
      B.S., Genetics and Plant Breeding, Haryana Agricultural University

    Dr. Raghvinder S. Sangwan is a professor of software engineering with expertise in the analysis, design, and development of large-scale, software-intensive systems and the use of AI engineering to design and develop intelligent systems that are safe, secure, and trustworthy. His research focuses on the improvement of these practices, and he has taught related courses to engineers and project managers at many prestigious academic, government, and industry organizations worldwide. Dr. Sangwan actively consults for Siemens Corporate Technology in Princeton, New Jersey, and holds a visiting scientist appointment at the Software Engineering Institute at Carnegie Mellon University in Pittsburgh, Pennsylvania. He is a distinguished contributor and senior member of IEEE and a senior member of ACM.

  • Satish Srinivasan

    • Degree
      Ph.D., Information Technology, University of Nebraska at Omaha
    • Degree
      M.S., Industrial Engineering and Management, Indian Institute of Technology, Kharagpur
    • Degree
      B.S., Information Technology, Bharathidasan University

    Dr. Satish Srinivasan is an associate professor of information science in the engineering division at Penn State Great Valley. He teaches courses related to database design, data mining, data collection and cleaning, design and implementation of predictive analytics system, network and web securities, and business process management. His research interests include social network analysis, data mining, machine learning, big data and predictive analytics, and bioinformatics.

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Ready to take the next step toward your Penn State master's degree?

Apply by April 15 to start May 13. How to Apply