Data Science, M.S.

(33 credits)

The Master’s degree in Data Science is designed to equip students with a comprehensive understanding of data analysis, programming, and machine learning techniques, preparing them for careers in various industries. This interdisciplinary program combines principles from mathematics, statistics, computer science, and artificial intelligence, enabling students to extract valuable insights from complex datasets.

Program Structure: The curriculum consists of 33 credit hours of core courses, providing foundational knowledge essential for data science.

Career Opportunities: Graduates of the Master’s degree in Data Science will be prepared for various career paths, including but not limited to:

Data Scientist: Analyzing complex datasets to extract meaningful insights and drive decision-making.
Data Analyst: Interpreting data to identify trends and provide actionable recommendations for business strategies.
Machine Learning Engineer: Developing and implementing machine learning models and algorithms to solve complex problems.
Data Engineer: Designing and maintaining data pipelines and databases to ensure efficient data processing and storage.
Business Intelligence Analyst: Utilizing data analysis and visualization techniques to support business operations and strategic planning.
Quantitative Analyst: Applying mathematical models to financial data to inform investment decisions and risk management.

This program prepares students for a dynamic and rapidly evolving field, ensuring they possess the skills needed to succeed in various roles across industries such as technology, finance, healthcare, and more.

Outcomes

Analyze and Interpret Complex Datasets: Apply advanced statistical, mathematical, and computational techniques to analyze large and complex datasets, drawing meaningful insights and making data-driven decisions across various fields.

Master Data Visualization and Communication: Create compelling data visualizations and effectively communicate analytical results to stakeholders, ensuring that complex data insights are clear, actionable, and relevant to diverse audiences.

Develop and Implement Predictive Models: Utilize machine learning, artificial intelligence, and statistical modeling techniques to build and deploy predictive models that solve real-world problems and support business or organizational strategies.

Design, Manage, and Query Databases: Demonstrate proficiency in designing, managing, and querying relational and NoSQL databases, ensuring efficient data storage, retrieval, and integration in a variety of applications.

Address Ethical, Legal, and Security Concerns in Data Science: Understand and navigate the ethical, legal, and cybersecurity challenges involved in data science, ensuring the responsible use of data in compliance with legal regulations and best practices for data protection.

Core Courses

College Algebra (Math 120 or similar), Beginning Stats (Math 223 or similar), and Intro to Programing (CSCI 170 or similar) are basic pre-requites for this program.

DATA 501/DATA 301	Introduction to Data Science	3
DATA 502	Introduction to Data Science Programming	3
DATA 503	Mathematics for Data Science	3
DATA 519	Introduction to Artificial Intelligence	3
DATA 540	Data Mining & Visualization	3
DATA 554	Database Management Systems	3
DATA 555	Advanced Database Management Systems	3
DATA 557	Introduction to Big Data Analytics	3
DATA 560	Text Mining and Language Processing	3
DATA 580	Principles of Cybersecurity	3
DATA 595	Data Science Capstone	3