M.A. in Nonprofit Leadership
The M.A. in Nonprofit Leadership at OCU is a 36-credit-hour program that can be complet...
M.S. in Data Analytics
Oklahoma City, Oklahoma
INTAKE: Jan, May & Aug
Program Overview
The M.S. in Data Analytics at OCU is a 30-credit-hour program offered in an on-campus format, with classes delivered in convenient 8-week blocks. It provides a comprehensive curriculum that prepares graduates to apply data analysis, visualization, and artificial intelligence prediction tools to meet pressing business challenges. Students delve into the fundamentals of programming for data science, data visualization, data engineering, forecasting, and predictive analytics, emerging well-prepared for diverse roles in data-driven decision-making. The program also allows students to choose nine credit hours from existing disciplines like MS in Accounting, MS in Financial Analytics, MBA in Leadership, or MBA in Health Care Administration, enabling further specialization.
STEM-Designated: A significant advantage of OCU's M.S. in Data Analytics program is its STEM (Science, Technology, Engineering, and Mathematics) designation. This is highly beneficial for international students, as it allows them to qualify for an extended Optional Practical Training (OPT) period in the U.S. by an additional 24 months, totaling up to 36 months of post-graduation work authorization. This extended period provides invaluable opportunities for practical experience and career development in the U.S. data analytics industry.
Curriculum: The curriculum is highly hands-on and technical, focusing on the practical application of data analytics tools and methodologies. Key courses include "Computer Programming for Data Scientists" (covering languages like Python or R), "Data Analysis for Business Decisions" (utilizing spreadsheet, statistical, and simulation software), "Data Visualization" (with tools like Tableau, PowerBI), "Data Engineering" (emphasizing relational databases like SQL SERVER, MySQL, Snowflake), "Forecasting" (including time series analysis), and "Predictive Analytics" (covering decision trees, regression, neural networks, and machine learning methods). The program also addresses "Big Data & Cloud Computing," ensuring students understand concepts, architectures, and tools for handling large datasets.
Research Focus: Oklahoma City University's Meinders School of Business, where the M.S. in Data Analytics program is housed, emphasizes an applied research focus. The university is home to the Ronnie K. Irani Center for Data Analytics and Artificial Intelligence. This center is dedicated to providing cutting-edge analytic solutions to industry leaders and academic visionaries. Faculty expertise includes areas such as health information technology, population health, social media analytics, human-AI interaction, AI aversion, and economic forecasting. The program encourages students to engage with real-world data problems and apply their analytical skills to solve practical business challenges, often through projects that leverage the center's resources and connections.
Industry Engagement: Oklahoma City University prioritizes strong industry engagement within its M.S. in Data Analytics program. The faculty members often possess extensive industry experience, bringing current best practices and real-world case studies directly into the classroom. The Meinders School of Business provides students with access to cutting-edge resources like the Bloomberg Finance Lab and fosters opportunities for interaction with local business leaders through various institutes and advisory boards. The program's hands-on approach and focus on industry-standard tools ensure that graduates are well-prepared to contribute immediately to data-driven roles across diverse sectors.
Global Perspective: The M.S. in Data Analytics at Oklahoma City University inherently incorporates a global perspective due to the universal nature of data and its applications across industries worldwide. While specific "global" courses might not be explicitly listed, the analytical techniques and tools taught are globally applicable. The program's STEM designation also attracts a diverse international student body, enriching classroom discussions with varied global viewpoints and experiences in data challenges. Graduates are prepared to work with global datasets, understand diverse market behaviors, and contribute to international teams, leveraging data to inform decisions on a global scale.
Location
Oklahoma City, Oklahoma
Score
IELTS 6.5
Tuition Fee
USD 14190
Postgraduate Entry Requirements
Academic Qualifications: Applicants for postgraduate programs typically require a minimum academic achievement of 70% 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 83 or higher.
- PTE: Overall score of 53 or higher.
- DET (Duolingo English Test): Minimum score of 105.
Oklahoma City University (OCU) offers a variety of scholarship opportunities designed to attract and support talented international students. These scholarships help reduce the financial burden of studying abroad and reward academic excellence, leadership, and artistic achievement.
Merit-Based Scholarships: OCU provides merit-based scholarships to international students who demonstrate outstanding academic records, leadership potential, and community involvement. These scholarships are automatically considered during the admission process, and amounts vary based on academic achievement and program of study.
Performance and Talent Scholarships: Students applying to OCU’s renowned performing arts programs, including music, dance, and theater, may be eligible for performance-based scholarships. These awards recognize exceptional artistic ability and provide financial support to help students pursue their creative passions at a professional level.
Transfer Student Scholarships: International students transferring from other accredited institutions may qualify for transfer scholarships. These awards acknowledge previous academic success and help make the transition to OCU more affordable.
Graduate Scholarships and Assistantships: Graduate students, especially those in business, law, and healthcare fields, can access scholarships and assistantships that offer tuition remission and stipends in exchange for teaching or research support. These opportunities provide valuable experience and financial relief.
Oklahoma City University's M.S. in Data Analytics is a highly technical and practical program designed to produce skilled data professionals. Its hands-on curriculum, focus on industry-standard tools, and particularly its STEM designation, make it a powerful credential for individuals seeking to enter or advance in the booming field of data science and analytics. Graduates are equipped to translate complex data into actionable insights, driving strategic decisions and creating significant value for organizations.
Data Scientist: This is a top-tier role involving the collection, analysis, and interpretation of large, complex datasets to extract deep insights. Data scientists build predictive models, apply machine learning algorithms, and develop custom analyses to solve critical business problems and inform strategic decisions across various industries.
Data Analyst: Collects, cleans, processes, and interprets data to identify trends, patterns, and insights. Data Analysts create reports and dashboards, and present findings to help organizations make data-driven decisions. They are crucial in virtually every sector, from marketing and finance to healthcare and human resources.
Business Intelligence (BI) Analyst/Developer: Focuses on turning raw data into meaningful insights that support business decision-making. BI analysts use tools like Tableau and Power BI to create interactive dashboards and reports, helping stakeholders understand performance, identify opportunities, and mitigate risks.
Data Engineer: Designs, builds, and maintains the robust infrastructure and systems required for collecting, storing, processing, and analyzing large datasets. They ensure data is accurate, accessible, and ready for use by data scientists and analysts, often working with cloud platforms and big data technologies.
Machine Learning Engineer: A specialized role that bridges data science and software engineering. Machine Learning Engineers design, build, and deploy machine learning models and AI systems. They work to create functional software that enables machines to make decisions and enhance user experiences, often in areas like personalized recommendations or predictive maintenance.
Quantitative Analyst (Quant): Primarily found in the finance and investment banking sectors, Quants use advanced mathematical, statistical, and computational methods to develop complex models for pricing financial instruments, managing risk, and devising trading strategies.
Marketing Analyst: Applies data analytics to understand consumer behavior, measure the effectiveness of marketing campaigns, and identify market trends. They use data to optimize marketing strategies, personalize customer experiences, and drive sales growth.
Operations Analyst: Utilizes data to optimize operational processes, improve efficiency, and reduce costs within an organization. This can involve analyzing supply chain data, production metrics, logistics, and resource allocation to streamline workflows and enhance performance.
Healthcare Data Analyst: Specializes in analyzing healthcare data (e.g., patient records, insurance claims, public health data) to improve patient care, manage costs, identify disease patterns, and enhance public health initiatives within hospitals, research institutions, and pharmaceutical companies.
Consultant (Data/Analytics): Works with diverse clients across various industries, providing expertise in data strategy, analytics implementation, and data-driven transformation. This role requires strong problem-solving skills, the ability to communicate complex findings to non-technical audiences, and adaptability to different business contexts.
