The demand for skilled data scientists and managers with the ability to use big data to add value to their organizations is growing fast and there’s never been a better or more exciting time to pursue a degree in this high-growth field.
Harrisburg University’s Master of Science (M.S.) in Analytics degree program is designed for students with a strong background in mathematics, computer science, engineering, or economics who are looking to learn the specific techniques and tools involved in analytics and the business skills to apply this knowledge effectively and strategically. Whether you’re looking to grow in your current position or branch off in a new direction, Harrisburg’s M.S. in Analytics will give you the practical skills and real-world experience you need to pursue a rewarding career in big data.
Supplemented by industry supplied projects, HU graduates will be exceptionally well equipped to harness and communicate the full value of data to the organizations they serve. This Harrisburg University master-of-science degree program is a powerful new entrant into the field of data analytics and is critical to developing the next wave of analytics professionals who will find themselves well-positioned to launch their careers.
Businesses today use data mining and analytics to drive pricing, marketing, R&D, finance, operations, logistics, risk management, and online activities. Graduates with a Master-of-Science (M.S.) degree in Analytics from Harrisburg University of Science and Technology will enter the workforce with the skills, confidence, and expertise required to succeed in today’s information-intensive world.
HU’s Master-of-Science in Analytics combines mathematical and statistical study with instruction in advanced computational and data analysis. Students learn to identify patterns and trends; interpret and gain insight from vast quantities of structured and unstructured data; and communicate their findings in practical, useful terms. The program is designed for students with a strong background in mathematics, computer science, engineering or economics who seek the specific techniques and tools involved in analytics and the business skills to apply this knowledge effectively and strategically.
All three areas of data analysis are studied: predictive (forecasting), descriptive (business intelligence and data mining), and prescriptive (optimization and simulation). HU’s comprehensive curriculum provides a broad perspective, teaching the skills necessary to be highly effective in solving real-world business challenges. Students learn that simple data analysis can be misleading, that large-scale problems are not amenable to naive solutions, and that working with unstructured field data is different than working with the results of a design experiment. Coursework covers everything from database management, statistical analysis, and data mining, to project management and business intelligence.
Carlos Muza / Unsplash
This 36-semester hour program prepares the student by providing depth in analytics during the first year and focused functional study during the second year that can be applied to any discipline or any interdisciplinary area. Data analysts are forging new relationships in virtually every discipline: business, healthcare, geology, mathematics and statistics, biology, chemistry, computer science, information systems and technology, engineering, psychology, behavioral science, operations research and more, in addition to potential interactions between these disciplines, using role-based interaction with information and analytics to enable highly- collaborative, data-driven organizations
The Analytics student will complete an individualized concentration.
ANMS graduates are able to:
- Identify and assess the opportunities, needs, and constraints for data usage;
- Make clear and insightful analyses changing direction quickly as required by these analyses;
- Measure, evaluate, and explain the level of quality of a dataset and develop a plan to improve the quality;
- Work effectively in a team to develop data analytics solutions;
- Recognize and analyze ethical issues related to intellectual property, data security integrity, and privacy; and
- Communicate clearly and persuasively to a variety of audiences.
Graduates become data scientists and analysts in finance, marketing, operations, and business intelligence working groups that generate and consume large amounts of data.
The following courses comprise the Master of Science in Analytics program - 36 semester hours. The semester hour value of each course appears in parentheses ( ).
Complete all of the following Core courses – 15 semester hours:
- ANLY 500 Analytics I: Principles and Applications (3)
- ANLY 502 Analytical Methods I (3)
- ANLY 506 Exploratory Data Analysis (3)
- ANLY 512 Data Visualization (3)
- ANLY 510 Analytics II: Principles and Applications (3)
- ANLY 545 Analytical Methods II (3)
- ANLY 560 Functional Programming Methods for Analytics (3)
Complete the following experiential courses – 6 semester hours:
- GRAD 695 Research Methodology and Writing (3)
- ANLY 699 Applied Project in ANLY (3)
- GRAD 699 Graduate Thesis (3)
The Master of Science in Analytics student can choose electives totaling 15 credits from any graduate-level program. This option allows Analytic students to build their own customized specialization and concentrations.
Email HMS@harrisburgu.edu to request program details and application instructions.
The admission process at HU is designed to help you make good decisions about your educational choices and to make sure you explore all the enrollment options at the University, so you find the plan that works best for you. The process is meant to be informative and encouraging–not to present an intimidating barrier to your educational plans. Just as every student receives personal attention in the classroom, every applicant receives thorough consideration and guidance during the enrollment process.
The University seeks students from a variety of backgrounds who can contribute to a vibrant and diverse University community. Students can demonstrate their academic potential through a variety of means. No one particular factor can measure a student’s potential, therefore the University gives consideration to all aspects of your admissions application.