Get started with MU
Apply hereMaster of science in data science and analytics
Learn to unlock the transformative possibilities of data for the health care and biohealth industries. The University of Missouri (Mizzou) adapts the online master of science in data science and analytics degree program to shifts in data usage and technologies, exposing professionals from a range of backgrounds and skill sets to the latest tools, techniques and industry-specific applications. The biohealth analytics emphasis area centers around the knowledge needed to draw insights from the growing amount of health care data available to shape patient care delivery, pioneer advancements through research, better understand the functions and behaviors of humans and diseases and ultimately change lives.
Mizzou’s online master’s in data science and analytics with an emphasis in biohealth analytics is geared toward curious, ambitious health care, population health and research professionals striving to drive innovation. This multidisciplinary program strengthens your foundational skills with a core covering key tools, mathematically rooted competencies and technologies like machine learning and visualization methods for communicating your findings to a range of audiences. In the process, you broaden what you know about big data’s applications and receive job-ready hands-on experience.
From here, you’ll explore data science and analytics’ applications in the medical, biohealth and health care fields through three courses immersing you in related technologies and standards. Hands-on learning is integrated from the start, with world-class faculty and industry leaders guiding your progress. You’ll then showcase the full breadth of your knowledge and acquired skills with a case study and capstone.
Explore other emphasis areas from Mizzou's master of science in data science and analytics:
Why earn a master’s degree in health data analytics?
As the 21st century moves forward, industries are uncovering a wealth of structured and unstructured data that can shape services and products, influence new initiatives and fuel research. The health care field is no different. In the present, hospitals routinely update electronic medical records, more personalized precision medicine continues to see a larger profile and biomedical data is increasingly integral to research-based sectors from public health to geonomics.
These developments have shed light on a need for professionals well-versed in data science and analytics’ applications and security requirements in the health care and biomedical field. Mizzou’s online master’s in data science and analytics with an emphasis in biohealth analytics prepares you for this responsibility through a technical core introducing you to key tools and an emphasis area exploring industry-specific applications. Our program was ranked No. 9 by Fortune.com for "Best Online Master's in Data Science Programs in 2023". This underscores Mizzou's mission to meet the high demand for training today's top data science professionals. As a student enrolled in the online program, you’ll:
- See what’s involved in examining and drawing insights from large data sets
- Begin to frame experiments around data science, from acquiring to analyzing data to presenting your results
- Learn how data analytics can solve a variety of health care and medical research problems
- Get hands-on experience in the full process of being presented with a problem to using data analytics and business intelligence tools to arrive at a conclusion
- Understand how data science and analytics can influence a spectrum of health care, population health and research decisions
- Become familiar with industry-specific ethics and security procedures for protecting sensitive data
- Be exposed to the full scope of modern data analytics, including its mathematical and statistical analysis foundation, technologies like machine learning and data mining, programming languages, data management, visualization and database systems
Quick facts
Official name
Master of science in data science and analytics with an emphasis in biohealth analyticsCampus
Program type
Master's degreeAcademic home
Graduate School | MU Institute for Data Science and InformaticsDelivery mode
100% onlineAccreditation
Higher Learning CommissionCredit hours
34Estimated cost
$33,422.00*This cost is for illustrative purposes only. Your hours and costs will differ, depending on your transfer hours, your course choices and your academic progress. See more about tuition and financial aid.
Career prospects
Continue growing your skills as a health care or research professional. Mizzou designed the online master’s in data science and analytics to help tomorrow’s workforce understand the power and specific applications of big data, from its capabilities to how findings can influence organization- and industry-level decision-making and outcomes.
The biohealth analytics emphasis focuses on these applications in the broad context of the health care field, including for hospitals, insurance companies, pharmacology, agriculture, research, health information systems, genomics, biomedical engineering, laboratories, public health, genetics and computational biology. With the Bureau of Labor Statistics predicting 9% growth for medical records and health information specialists between 2020 and 2030, potential job titles include:
- Operations research analyst
- Biomedical informatics
- Nurse informatics
- Data science analyst
- Performance analyst
Program structure
The online master’s in data science and analytics involves 34 credit hours, including core courses (19 credit hours), an emphasis area (nine credit hours), a case study (three credit hours) and a capstone project (three credit hours). Core and emphasis area courses are structured in eight-week modules, allowing students to finish the program in about two years.
You’ll take 100% of your courses online and have the option to attend an on-campus Data Science Week in the spring, where you can work closely with world-class faculty members. The program is semester-based.
Core courses serve as a multipart introduction to what data science and analytics are, their mathematical foundation and essential tools. During this sequence, you’ll learn to access, cleanse, model, interpret and visualize data and understand the statistical analysis skills needed to draw insights. From here, the core courses go over the basics of database systems, query methods and visualization techniques, ethics in industry, business, research and academia, applied machine learning and modeling, and security processes for data collection, storage and processing. You’ll practice all of these skills throughout the program.
A case study followed by a capstone requires you to apply your biohealth data science and analytics knowledge to a real-world problem. The eight-week summer group case study serves as preparation for the capstone, during which you’ll collaborate with faculty and industry leaders to analyze large, complex data sets.
Biohealth analytics courses
As you transition to the emphasis area, you’ll explore data science and analytics in the context of processing, mining and assessing medical records, genomics data and other health care information. Courses go over:
- The foundation of genomics and bioinformatics, including analyzing DNA, genes and proteins
- Health care data science, including regulations, dissemination and statistical analysis involving health data
- Advanced health data science, including in the context of research, clinical trials and machine learning
Delivery
100% onlineCalendar system
Semester-basedTypical program length
2 yearsAccreditation
The University of Missouri is accredited by the Higher Learning Commission, one of six regional institutional accreditors in the United States.
Faculty spotlight
Blaine Reeder uses human-centered design methods for informatics research that supports the health-related activities of patients, family members, care teams and researchers. Dr. Reeder’s primary research focus is the design and integration of information from smart homes, wearable devices, mobile apps and electronic health records as components of translational research infrastructure to support healthy aging.