Master of Business Administration (MBA)
The Master of Business Administration (MBA) program at Southwest Minnesota State Univer...
B.S. in Data Science
Marshall, Minnesota
INTAKE: Jan & Aug
Program Overview
The B.S. in Data Science at Southwest Minnesota State University (SMSU) is designed to equip students with comprehensive skills in data analysis, statistical modeling, and computational techniques. This program prepares graduates to manage and interpret complex data sets, make data-driven decisions, and solve real-world problems using cutting-edge technology. Emphasizing both theoretical knowledge and practical experience, the program aims to address the growing demand for skilled data professionals in various industries.
STEM-Designated: The B.S. in Data Science is recognized as a STEM (Science, Technology, Engineering, and Mathematics) program, reflecting its focus on quantitative and analytical skills. This designation highlights the program’s emphasis on rigorous mathematical and statistical methods, computational techniques, and technology-driven solutions, ensuring graduates are well-prepared for technical roles in the data science field.
Curriculum: The curriculum for the B.S. in Data Science is designed to provide a solid foundation in both the theoretical and practical aspects of data science. Core courses typically include subjects such as statistical analysis, data mining, machine learning, data visualization, and database management. Students also engage in programming courses focusing on languages such as Python and R. The program often includes capstone projects or internships, allowing students to apply their knowledge in real-world settings and gain hands-on experience.
Research Focus: Research within the B.S. in Data Science program often revolves around innovative approaches to data analysis, machine learning, and predictive modeling. Students and faculty collaborate on projects that explore new methods for handling big data, developing algorithms, and addressing complex problems across various domains such as healthcare, finance, and environmental science. The research focus is designed to keep pace with advancements in data science and contribute to the development of novel solutions and technologies.
Industry Engagement: The B.S. in Data Science program at SMSU emphasizes strong industry engagement through partnerships with local and regional businesses, internships, and collaborative projects. Students benefit from opportunities to work on real-world data challenges, interact with industry professionals, and gain insights into the practical applications of data science. These connections help students build a professional network and enhance their employability upon graduation.
Global Perspective: The program incorporates a global perspective by addressing the international dimensions of data science, such as global data privacy regulations, cross-cultural data analysis, and the use of data science in solving global issues. Students are encouraged to consider the global impact of data science practices and to be aware of diverse data-related challenges and opportunities worldwide.
Location
Marshall, Minnesota
Score
IELTS 6
Tuition Fee
USD 10304
Undergraduate Entry Requirements
Application Fee: $100
Academic Qualifications: Applicants for undergraduate programs typically require a minimum academic achievement of 65% or above in their previous academic qualifications.
English Language Proficiency:
- IELTS: Overall band score of 6.0 with a minimum of 5.5 in each component.
- TOEFL: Overall score of 61 or higher.
- PTE: Overall score of 47 or higher.
- DET (Duolingo English Test): Overall score of 100.
Scholarships that Southwest Minnesota State University (SMSU), USA, typically offers to international students.
International Student Scholarships: SMSU often provides scholarships specifically designed for international students to help offset the cost of tuition. These scholarships are typically merit-based and may consider factors such as academic achievement, standardized test scores, and extracurricular involvement.
Presidential Scholarships: The Presidential Scholarship is one of the most prestigious scholarships offered by SMSU. It is often awarded to outstanding students, including international students, who have demonstrated exceptional academic performance. The scholarship typically covers a significant portion of tuition costs.
Dean's Scholarships: Dean's Scholarships are often available to high-achieving international students who have a strong academic record. These scholarships are typically competitive and may vary in amount.
Transfer Student Scholarships: SMSU may offer scholarships specifically for international transfer students who are transferring from another institution. These scholarships can help make the transition to SMSU more affordable.
Departmental Scholarships: Some academic departments at SMSU may offer departmental scholarships to international students pursuing specific majors or fields of study. These scholarships are often based on academic merit and may require students to meet certain criteria.
Cultural Exchange Scholarships: SMSU may participate in cultural exchange programs that provide scholarships to students from partner institutions abroad. These scholarships aim to promote international exchange and cultural understanding.
External Scholarships: In addition to university-sponsored scholarships, international students at SMSU may also be eligible for scholarships from external organizations, foundations, or government agencies. These scholarships can be a valuable source of financial aid.
Please note that scholarship offerings, eligibility criteria, and award amounts may change over time.
Graduates of the B.S. in Data Science program from Southwest Minnesota State University (SMSU) have a wide range of career opportunities available to them due to the program's focus on equipping students with advanced data analysis, statistical, and computational skills. The growing importance of data-driven decision-making in various sectors ensures that these graduates are in high demand.
Data Analyst: Data Analysts are responsible for interpreting complex data sets to help organizations make informed decisions. They use statistical tools to identify trends, create visualizations, and provide actionable insights based on data.
Data Scientist: Data Scientists leverage their expertise in programming, statistics, and machine learning to build predictive models and algorithms. They work with large datasets to extract meaningful patterns and support strategic planning and decision-making processes.
Business Intelligence (BI) Analyst: BI Analysts focus on analyzing data to help businesses understand their market performance and operational efficiency. They design and implement data models, dashboards, and reports to inform business strategies.
Machine Learning Engineer: Machine Learning Engineers develop algorithms and models that enable systems to learn from data and improve over time. They apply techniques such as deep learning and reinforcement learning to solve complex problems and optimize processes.
Data Engineer: Data Engineers are responsible for designing, building, and maintaining data pipelines and infrastructure. They ensure that data is accurately collected, stored, and processed, enabling efficient data analysis and reporting.
Quantitative Analyst: Often employed in financial sectors, Quantitative Analysts use mathematical and statistical models to analyze financial data, manage risk, and support investment decisions.
Data Consultant: Data Consultants provide expert advice to organizations on how to leverage data for business improvement. They analyze data needs, recommend solutions, and help implement data strategies.
Research Scientist: In various research domains, Research Scientists use data science techniques to conduct studies, analyze experimental results, and contribute to scientific knowledge across fields such as healthcare, environmental science, and engineering.
Data Visualization Specialist: Data Visualization Specialists focus on creating compelling visual representations of data to communicate complex information effectively. They design charts, graphs, and dashboards to help stakeholders understand insights.
Operations Analyst: Operations Analysts use data to evaluate and improve organizational processes and efficiency. They identify areas for improvement and implement data-driven solutions to optimize operations.
