Master’s in Mathematics | Northwest Missouri State University
“No human investigation can be called real science if it cannot be demonstrated mathematically.”
Leonardo da Vinci
Artificial Intelligence Machine learning, neural networks, and natural language processing. Exploring how models learn from data, how their predictions are evaluated, and the mathematics behind intelligent systems.
Group Theory Groups, symmetries, and the structures that describe transformations. Studying how abstract patterns connect geometry, algebra, and computation, with an interest in symmetry-aware approaches to machine learning.
Data Science Statistical inference, exploratory analysis, and predictive modeling. Turning raw data into reproducible analyses, testing assumptions, and communicating findings that support informed decisions.
Linear Algebra Vector spaces, matrix decompositions, eigenvalues, and linear transformations. The foundation for understanding embeddings, dimensionality reduction, and the computations at the heart of modern AI and data science.
Real Analysis Limits, continuity, convergence, and the rigorous foundations of calculus. Studying how precise definitions and proofs explain the behavior of functions, sequences, and the methods used in mathematical modeling.
Graph Theory Networks, connectivity, paths, and combinatorial structures. Exploring how relationships can be modeled and analyzed, from algorithmic problems to network data and graph-based machine learning.
Topology Continuity, connectedness, compactness, and the structure of spaces. Investigating properties preserved under continuous transformations, with an interest in how shape and structure inform the analysis of data.
- Python — analysis, automation, and problem solving
- SQL — querying, data exploration, and workflow support
- Pandas / NumPy
- Jupyter Notebooks
- Data-focused software development
- Building projects with Python and SQL for Financial Services
- Strengthening my data and analytics workflows
- Exploring the intersection of mathematics, data, and software
I value clarity, structure, and elegant solutions. Whether I’m working through a proof, a dataset, or a programming problem, I like approaches that are both rigorous and practical.
If you'd like to connect, feel free to send me a message on my personal website at dsmorgan.com/learn-more.