MAEd in Reading/Literacy
Maryville University, located in St. Louis, Missouri, USA, offers a Master of Arts in E...
M.S. in Data Science
St. Louis, Missouri
INTAKE: Jan & Aug
Program Overview
Maryville University, located in St. Louis, Missouri, USA, offers a Master of Science (M.S.) in Data Science. This program is meticulously crafted to prepare students for leadership roles in the rapidly expanding field of data science, which combines business acumen, statistics, artificial intelligence (AI), and machine learning. The program emphasizes hands-on, experiential learning, equipping graduates with the skills to recognize trends in complex data structures and make data-driven decisions across various professional fields, including business, engineering, health, social sciences, and computer science.
STEM-designated: Yes, Maryville University's M.S. in Data Science program is STEM-designated. This is a significant advantage, particularly for international students on an F-1 visa, as it allows for an extended Optional Practical Training (OPT) period of up to 36 months after graduation. This designation underscores the program's rigorous quantitative and analytical focus, highlighting its emphasis on technical proficiency in programming, machine learning, and statistical modeling.
Curriculum: The M.S. in Data Science program at Maryville is a 36-credit hour program (12 courses), designed for completion within approximately four semesters, or potentially three semesters through an accelerated option for qualified Maryville undergraduates. The curriculum is comprehensive, covering essential programming languages and advanced analytical techniques. Core courses include Math Modeling, R Programming, Python, SQL, SAS Programming, Machine Learning, Predictive Modeling, and a Capstone Project. Electives allow for specialization in areas such as NoSQL Databases, Text Mining, Big Data Analytics, Experimental Design, Deep Learning, Data Visualization, and Blockchain. The program emphasizes project-based learning, allowing students to apply theoretical knowledge to real-world data science problems.
Research Focus: Maryville University's M.S. in Data Science program integrates a strong research focus by preparing students to analyze and interpret complex data to advance human capabilities. The program's culminating Capstone Project is a significant research-oriented component, where students engage in the entire process of solving a real-world data science problem, from data collection and processing to applying suitable analytical methods. The curriculum includes courses in advanced statistics and mathematical modeling, essential for understanding the theoretical underpinnings of data science. Faculty members are actively involved in modernizing the curriculum and tools, often leveraging their expertise in areas like AI, machine learning, and big data to guide student projects and research.
Industry Engagement: Maryville University's M.S. in Data Science program boasts robust industry engagement, actively collaborating with corporate and civic organizations in the St. Louis region and beyond. The curriculum is developed in partnership with industry leaders to ensure it reflects the field's most sought-after skills, directly addressing the needs of employers. The program emphasizes experiential learning, integrating current or previous professional positions into the active learning curriculum. Opportunities for hands-on involvement in real-world projects, through avenues like the Capstone Project and professional partnerships with companies such as Fireman's Fund Insurance Company, Northwestern Mutual, Edward Jones, JPMorgan, and Allstate, provide students with invaluable practical experience and networking opportunities. Maryville also fosters engagement through its Data Science Club and Data Science Career Fair.
Global Perspective: The M.S. in Data Science program at Maryville University inherently fosters a global perspective by addressing the universal applicability of data science in today's interconnected world. Data collection and interpretation are global phenomena, benefiting industries and organizations worldwide. The program prepares graduates to work with big data, machine learning, and AI, which are transformative technologies impacting global economies and societies. While the program does not explicitly feature international study abroad components, the skills learned in programming, data mining, and predictive modeling are highly transferable across international borders. The university's diverse student body and faculty further enrich the learning environment, preparing students to work effectively in a globalized workforce where data-driven insights often inform international strategies.
Location
St. Louis, Missouri
Score
IELTS 6.5
Tuition Fee
USD 16700
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 92 or higher.
- PTE: Overall score of 62 or higher.
- DET (Duolingo English Test): Minimum score of 115.
Maryville University in the United States offers a variety of scholarship opportunities specifically designed for international students to help make higher education more affordable and accessible. Recognizing the diverse backgrounds and talents of its global student community, Maryville provides merit-based and need-based scholarships that reward academic excellence, leadership, and community involvement.
Merit-Based Scholarships: International students applying to Maryville University are automatically considered for merit scholarships based on their academic achievements, standardized test scores, and overall application strength. These scholarships can significantly reduce tuition costs and are renewable for multiple years provided students maintain satisfactory academic performance.
International Student Scholarships: Maryville offers exclusive scholarships tailored for international students to encourage global diversity and inclusion. These scholarships support students from various countries and academic disciplines, promoting cultural exchange and enriching the university community.
Program-Specific Scholarships: Certain colleges and departments within Maryville University provide scholarships targeted at students enrolled in specific programs such as business, nursing, education, and technology. International students pursuing degrees in these areas can apply for additional funding opportunities aligned with their fields of study.
A Master of Science (M.S.) in Data Science from Maryville University is a highly strategic and in-demand degree in today's data-driven world. This STEM-designated program is meticulously designed to equip graduates with the cutting-edge skills needed to analyze complex data structures, identify trends, and make data-driven decisions across diverse sectors, including business, healthcare, finance, and technology. With a strong emphasis on hands-on, project-based learning and preparation in essential programming languages and analytical techniques.
Data Scientist: This is the most direct and sought-after role. Data Scientists build predictive models, develop machine learning algorithms, and apply advanced statistical methods to extract actionable insights from large datasets, driving strategic decision-making in various industries.
Machine Learning Engineer: These professionals design, build, and deploy machine learning models and AI systems. They are skilled in programming, algorithm development, and ensuring that machine learning solutions are integrated effectively into existing applications and infrastructure.
Data Analyst: While often an entry-level role, an M.S. in Data Science elevates a Data Analyst's capabilities. They collect, clean, and interpret data to identify trends, create reports, and visualize findings to support business operations and inform decision-making.
Business Intelligence (BI) Developer/Analyst: These roles focus on creating and managing BI solutions, including dashboards, reports, and data visualizations, to help organizations understand their performance and identify areas for improvement. They translate complex data into accessible business insights.
Big Data Engineer: Specializing in managing and optimizing large-scale data infrastructures, Big Data Engineers design, build, and maintain data pipelines, ensuring that data is efficiently collected, stored, processed, and made accessible for analysis by data scientists and analysts.
Quantitative Analyst (Quant): Particularly in finance and investment, Quants use sophisticated mathematical and statistical models, often incorporating machine learning, to analyze financial markets, assess risk, and develop trading strategies.
Deep Learning Engineer/Researcher: This specialized role focuses on developing and applying deep learning models, a subset of machine learning, for tasks such as image recognition, natural language processing, and advanced predictive analytics.
Operations Research Analyst: These professionals use advanced analytical methods, including optimization and simulation, to solve complex operational problems, improve efficiency, and make better decisions in areas like logistics, supply chain management, and resource allocation.
AI/Machine Learning Consultant: Graduates can work as consultants, advising various organizations on how to leverage AI and machine learning technologies to solve business challenges, improve processes, and gain a competitive edge.
Product Manager (with Data Science Focus): In technology companies, product managers with a data science background use data analytics to inform product strategy, identify user needs, track product performance, and drive the development of data-driven features and functionalities.
