M.S. Statistics and Data Science Curriculum

In LMU’s Statistics and Data Science graduate program, you'll develop expertise in statistics, machine learning, artificial intelligence, and computational methods.

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Learning Outcomes

As a graduate of LMU’s Statistics and Data Science master’s program, you will be able to:

• Demonstrate a deep understanding of probability and statistical theory as the foundation for statistical inference
• Apply linear algebra, gradient-based methods, and optimization theory as essential foundations for representation learning and model training in machine learning and deep learning
• Manage complex and large-scale datasets and apply programming tools such as R and Python to implement statistical and machine learning methods efficiently
• Formulate research questions, apply appropriate analytical methods, and conduct independent or collaborative research projects to address real-world problems in fields such as biomedical science, business, social science, and environmental studies
• Communicate statistical and analytical findings clearly and effectively through oral presentations, written reports, and data visualizations
• Recognize ethical issues in data collection, analysis, and reporting, and apply principles of privacy, reproducibility, and responsible AI

Curriculum Structure

You can customize the Statistics and Data Science program to your personal interests and career aspirations. The program requires 30 units and is broken into two main sections:

• Required courses (16 units)
• Electives (14 units)

You can choose from interdisciplinary electives from Computer Science, Business, Economics, and Environmental Science.

Courses

Required courses may include: 

• Statistical Theory
• Regression Methods
• Deep Learning
• Foundations of Machine Learning

Sample elective courses may include:

• Computational Topics in Statistics
• Large Language Models
• Data Mining and Pattern Analysis
• Data Visualization and Geographic Information Systems
• Text-Mining and Social Media Analytics
• Machine Learning
• Natural Language Processing and Large Language Models
• Advanced Econometrics
• Spatial Data Analysis and Geographical Information Systems

Visit the LMU Bulletin to see a full list of classes available and course requirements for Statistics and Data Science.