Develop the knowledge and skills necessary to meet the growing demand for data science experts in the context of ongoing digital transformation and artificial intelligence.
Mississippi State University uniquely approaches data science as the field that advances methods to improve the use of data for human progress. Specifically, these methods allow humans to:
This definition of data science places the data lifecycle within a contextual framework (see diagram above) that emphasizes the role of scientific innovation (A.I. and Computing), people (workforce education and data science literacy), governance (ownership, privacy and confidentiality, and policy), infrastructure (hardware, software, network, storage, and security), ethics (the avoidance of algorithmic bias and a cultural mindset to use data to promote human flourishing), and the strategic goals that guide organizations in specific domains.Read more about how MSU defines data science (PDF).
The MSU Bachelor of Science in Data Science includes three general areas of coursework: general education to develop critical thinking and writing skills; a program core of computer science, statistics, mathematics, business information systems, and communications skills; and applications of the data science fundamentals in a specific concentration. Currently, the program offers 10 concentrations.
Modern enterprise management presents complex challenges of identifying actionable knowledge derived from the emerging flood of new data captured by an exploding number of online processes and connected sensors and devices. Companies are redesigning their organizational structures and processes to leverage this new capability – the concentration in BIS will prepare students to play a leading role in this emerging digital transformation and help companies compete in the increasingly connected environment. Students who complete the concentration will be prepared to solve business problems and identify business opportunities in the context of intelligent data analytics and digital transformation.
Data science increasingly drives innovation in the fields of agriculture and natural resources. The Computational Agriculture and Natural Resources concentration trains students interested in data-driven careers in agriculture and natural resources through subject matter and applied data science coursework. Students who complete the concentration will be equipped for careers as data scientists in agricultural production, agricultural technology, agricultural finance, natural resource management, wildlife and fisheries science, plant science, and other related fields.
Computational Intelligence focuses on understanding artificial intelligence and machine learning approaches to develop effective strategies to solve large-scale data science problems. This includes creation of new software tools, algorithms, and using existing programs and libraries. The concentration includes foundational courses in software development, algorithms, artificial intelligence, and machine learning. These ideas are then applied in various computer science-related contexts in upper-level courses and in a two-semester practicum.
Many human challenges are location specific. The Geoinformatics concentration prepares students to perform statistical analysis of geospatial data, analyze and visualize spatial data using Geographic Information Systems (GIS), and acquire spatial information from remote sensing platforms. Students who complete the concentration will be prepared for careers in the fields of meteorology/climatology, geospatial science, geology, or within any scientific field that relies on the collection and interpretation of spatial information.
Marketing and supply chain functions are increasingly driven by data. Tasks such as analyzing online social media content, planning advertising campaigns across multiple online channels, designing cutting edge products, and delivering products through complex global supply chains, all require cutting edge data analytics skills. Students who complete the concentration in Marketing and Supply Chain Analytics will be equipped to solve data-driven business problems relating to marketing and supply chain management.
Psychoinformatics is subfield of psychology for the acquisition, organization, and synthesis of data collected from psychology to reveal information about psychological traits such as personality and mood. Psychology, which historically acquired data from experiments and questionnaires, has been digitally transformed to overcome the problem of small sample sizes, bias, and unreliable memory. Psychoinformatics stores Big Data related to psychology (such as communications on smartphones, social media data, and even controlled online experiments), mines these data for relevant psychological information, and applies advanced analytical techniques to improve understanding. This concentration prepares students to apply data science to the field of psychology and prepares students for more advanced work with cognitive science and psychology.
Quantum computing, a new paradigm for computing that depends upon the quantum properties of reality, holds great promise for applications to data science including cryptography, deep learning, and simulation. Fundamental physics courses provide a discipline-specific foundation for quantum theory. Core concentration courses prepare students to understand and work with quantum computing, an inherently statistical approach to computational problem solving. Students who complete the concentration will possess not only a firm foundation in classical computing from the Data Science program as a whole, but will be ready to engage quantum computing as the next generation of enabling technologies for exciting applications such as AI.
Though the Quantum Computing concentration is currently at the proposal stage, all data science students will engage quantum computing in the lab DSCI 2022 Cloud, Quantum, and High-Performance Computing.
In this highly theoretical and forward looking field, many positions exist within research and development groups. Nascent occupations include:
Social media has transformed marketing, politics, commerce, and human relationships. The Social Data Analytics concentration prepares students to apply data science to understand sociological and political aspects of social media communication. Fundamental discipline courses lay discipline-specific foundations in social science. Core concentration courses prepare students for more advanced analysis work with social media sources. Students who complete the concentration will be able to leverage social media data to gain insight, make predictions, and influence the future of social collaboration.
The Sports Science concentration focuses on applying data science to understand the physiological and neuromechanical stresses on athletes. Students will apply data science techniques with foundational exercise science knowledge to assess physiological and neuromechanical variables and then interpret findings to improve training and performance. Students completing the Sports Science concentration will be prepared for careers working with individuals in a wide variety of sport and performance settings.
The Statistical Modeling concentration prepares students to apply advanced statistical methods to build analytical and statistical models. The concentration focuses on statistical models and methods that are needed to discover, validate, and predict patterns using large datasets (big data). Students completing the concentration will be able to apply the theoretical machinery of quantitative methods to the solution of real-world problems involving big data in many fields.
Two primary forces drive the rapid digital transformation of the design and construction process for the built environment: architects and designers are increasingly adopting Building Information Modeling (BIM) techniques to achieve more sustainable, accurate, and efficient design, planning, evaluation, and construction; and new intelligent building systems integrate Internet-of-Things (IoT) sensors to track every aspect of building performance. Students who complete the Visualization and Visual Analytics for the Built Environment concentration will be able to meet the design and construction industry’s need for new professionals who can bring together computational statistics and data analytic skills with visualization skills to inform the development of new workflows and strategies.
Mississippi State University's Bachelor of Science in Data Science leverages concentrations as a way to ensure that students pair the fundamental knowledge and skills of data science with substantive expertise in a particular field of study. The introduction of new concentrations is influenced by three key groups: industry partners who require MSU graduates capable of addressing the world's most critical issues; faculty and staff who foresee the significance of data science expertise in specific areas; and prospective students who are beginning to chart a course in life that will allow them to engage meaningful work that promotes human flourishing.
If you have an idea for a new concentration, please email us at firstname.lastname@example.org. We are looking forward to learning more about the challenges we can tackle together through data science.
Famously, Drew Conway described data science using a Venn diagram that made "substantive expertise" a key component of data science. While the field of data science itself engages discipline-specific research questions, it primarily exists within all disciplines as a way of pursuing scholarship. This means that data science experts must "know their stuff" in particular disciplines in order to ask the right questions and engage critical challenges intelligently.
Data scientists are not mere methodologists or mindless empiricists. They develop instincts in using data to solve challenges in specific fields. This is why the MSU Bachelor of Science in Data Science leverages concentrations to produce the experts who will be able to meet today's and tomorrow's challenges.
To inquire about enrolling in the Bachelor of Science in Data Science, including dual-degree opportunities to combine Data Science with other majors and 4+1 opportunities to combine a Bachelor of Science in Data Science with a Master of Science in Business Administration, Computer Science, or other fields, please contact:
Data Science Academic Coordinator