Education

The University of Kansas

Bachelor's of Science in Computer Science, Minoring in Businesss, Class of '25 - Undergraduate Research (UGR) Fellow with Multiple Honor Roll Distinctions

Key Courses (All A grades)

  • MATH 125-127: Calculus I, II, and III
  • EECS 210: Discrete Structures
  • MATH 290: Linear Algebra
  • EECS 330: Data Structures and Algorithms
  • EECS 388: Embedded Systems

Certification

Coursera, Stanford University, DeepLearning.AI

Machine Learning Specialization

Key Concepts

  • Learned to build and train supervised models for prediction & binary classification tasks (linear, logistic regression) using NumPy and scikit-learn.
  • Learned to build and train neural networks with TensorFlow to perform multi-class classification, (as well as decision trees and ensemble methods).
  • Learned to apply best practices for ML development and use unsupervised learning techniques including clustering & anomaly detection.