Develop the knowledge and skills necessary to meet the growing demand for data science experts in the context of ongoing digital transformation.
Data science is a new emerging field that explores and advances methods, systems, and processes to:
The MSU Bachelor of Science in Data Science is an interdisciplinary program designed to include 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 9 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.
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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.
Psycho-informatics 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. Psycho-informatics 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.
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 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.
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:
Lynn Taylor
Data Science Academic Coordinator
clj19@msstate.edu
(662)-325-3168