M.A. in English
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M.S. in Applied Data Analytics
Conway, Arkansas
INTAKE: August
Program Overview
The MS in Applied Data Analytics at UCA is a 30-semester-hour graduate program that prepares students for employment in managing, using, and exploiting data to enhance decision-making within organizations. It is particularly beneficial for individuals seeking to transition into data-centric careers or to augment their existing skill sets with advanced analytical capabilities. The program offers a solid foundation in the technical aspects of data analytics, covering a broad range of common skill areas. It is designed to be completed within 18 to 24 months for full-time students.
STEM-Designated: While the search results show an MS in Applied Data Analytics from the University of Detroit Mercy is STEM-designated, and generally, most Applied Data Analytics programs in the US are STEM-designated due to their heavy reliance on quantitative methods and technology, specific confirmation for UCA's MS in Applied Data Analytics being STEM-designated is not explicitly stated in the provided search results. However, given the nature of data analytics as a field that applies scientific methods, processes, and systems to extract knowledge from data, it is highly likely to be considered a STEM field. Students interested in this program, especially international students, should verify its STEM designation directly with UCA's admissions office for clarity on OPT extensions.
Curriculum: The curriculum for the MS in Applied Data Analytics requires 30 semester hours of graduate work, including a core of 24 hours and an additional 6 hours of electives. Core courses often include those in critical thinking in data analytics, prescriptive analytics, business intelligence and data visualization, data mining and applied analytics, predictive analytics, and Python for data analytics. The program's structure allows students to gain foundational work in all common skill areas of data analytics. Elective options may cover areas like information technology for managers, seminar in accounting information systems, project management leadership, simulation and modeling in data analytics, SQL for data analytics, data management, and internships. This comprehensive approach ensures graduates possess a well-rounded understanding of data analytics principles and tools.
Research Focus: The research focus within the MS in Applied Data Analytics program at UCA is inherently applied, concentrating on leveraging data to solve real-world business problems and enhance decision-making. The curriculum emphasizes effectively using data by building expertise in areas such as data management and cleansing, descriptive, predictive, and prescriptive analytics, advanced statistics, and data mining. While not a traditional academic research program, the coursework involves practical projects and case studies where students apply analytical techniques to extract insights and develop solutions, effectively engaging in "applied research" within a business context. Some elective options might also include an "Applied Data Analytics Project" or an "Internship in Data Analytics," providing hands-on research and application experience.
Industry Engagement: The program at UCA is designed with a keen awareness of industry needs. The curriculum directly addresses the growing demand for data analytics experts in various business functions, including accounting, management, marketing, and finance. While explicit details on specific industry partnerships or guest speaker series are not provided in the search results, the program's practical orientation and focus on "applied" analytics suggest a strong alignment with industry requirements. The availability of internship opportunities further indicates a commitment to connecting students with real-world industry experience, preparing them for immediate impact upon graduation.
Global Perspective: The skills acquired in the MS in Applied Data Analytics program are highly relevant in the globalized business environment. As companies worldwide increasingly rely on data for strategic purposes, the ability to manage, analyze, and interpret data effectively is a universal demand. UCA's College of Business, which houses this program, has a stated mission to "educate a diverse population of current and future business professionals to successfully and ethically meet the challenges of the global business environment." This overarching commitment ensures that the data analytics curriculum, while grounded in practical applications, also considers the broader implications and ethical considerations of data usage in an interconnected global economy.
Location
Conway, Arkansas
Score
IELTS 6.5
Tuition Fee
USD 11400
Postgraduate Entry Requirements
Application Fee: $50
Academic Qualifications: Applicants for postgraduate programs typically require a minimum academic achievement of 65% or above in their bachelor's degree.
English Language Proficiency:
- IELTS: Overall band score of 6.5 or 7.0 with a minimum of 6.0 in each component.
- TOEFL: Overall score of 79 or higher.
The University of Central Arkansas (UCA) offers a variety of scholarship opportunities for international students to help make higher education affordable and accessible. These scholarships recognize academic excellence, leadership, and community involvement, supporting talented students from around the world as they pursue their degrees.
Merit-Based Scholarships: UCA provides competitive merit scholarships specifically for international students, awarded based on academic achievements such as high school GPA, standardized test scores, and other accomplishments. These scholarships can significantly reduce tuition costs and are renewable each year, provided students maintain satisfactory academic performance.
International Student Scholarship: The university offers dedicated scholarships for international students, including awards that cover partial tuition fees. These scholarships aim to attract high-performing students globally and promote diversity on campus.
Program-Specific Scholarships: Some colleges and departments within UCA provide scholarships for international students pursuing specific fields of study, such as business, education, health sciences, or the arts. Prospective students are encouraged to inquire about scholarships related to their major.
An M.S. in Applied Data Analytics from the University of Central Arkansas (UCA) equips graduates with highly sought-after skills in data management, analysis, interpretation, and visualization. In today's data-driven world, these competencies are critical across virtually every industry, making graduates versatile and in high demand for a wide array of career opportunities.
Data Analyst: This is a foundational role where graduates collect, clean, analyze, and interpret large datasets to identify trends, patterns, and insights. They often create reports and visualizations to communicate their findings to stakeholders, supporting data-driven decision-making across various departments.
Business Intelligence (BI) Analyst: BI Analysts focus on transforming raw data into actionable business insights. They develop dashboards, reports, and data models that help organizations understand their performance, identify opportunities, and make strategic decisions.
Data Scientist: Often considered a more advanced role, Data Scientists build predictive models, develop algorithms, and apply machine learning techniques to extract deeper insights from data. They use statistical modeling and programming (often Python or R) to forecast trends, identify complex relationships, and solve intricate business problems.
Analytics Manager: With experience, graduates can advance to management roles, leading teams of data analysts or data scientists. They are responsible for overseeing analytics projects, setting data strategy, and ensuring that data insights are effectively integrated into business operations.
Marketing Analyst: In this role, graduates apply data analytics to understand consumer behavior, measure the effectiveness of marketing campaigns, and optimize marketing strategies. They analyze customer data, website traffic, and campaign performance to drive better marketing ROI.
Financial Analyst (with Data Analytics Focus): Financial analysts who specialize in data analytics use large financial datasets to forecast economic trends, assess risk, detect fraud, and optimize investment portfolios. Their data skills enhance traditional financial analysis.
Operations Analyst: These professionals use data to optimize business processes, improve efficiency, and reduce costs within an organization's operations. They might analyze supply chain data, production metrics, or logistics information to identify bottlenecks and suggest improvements.
Healthcare Data Analyst: With the massive amount of data generated in healthcare, analysts are crucial for improving patient outcomes, optimizing hospital operations, managing costs, and conducting research. They analyze patient records, clinical trials data, and public health statistics.
Consultant (Data/Business Analytics): Graduates can work for consulting firms, advising various clients across industries on how to leverage their data more effectively. This involves identifying data challenges, designing analytical solutions, and implementing data-driven strategies.
Research Analyst (Quantitative/Statistical): In academic, government, or research institutions, graduates can contribute to studies that rely heavily on quantitative analysis. They apply statistical methods and data modeling to answer research questions and publish findings.
