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COURSEWORK
Learn more about courses related to my fields of study at Rice University.
Major: Statistics and Sport Analytics
Minor: Data Science
RELEVANT COURSES
SUMMER 2025
CMOR 438: DATA SCIENCE & MACHINE LEARNING
Reviewed online lectures and applied my knowledge of relevant topics by building a comprehensive GitHub repository that implemented a variety of essential machine learning algorithms. The course emphasizes essential algorithms, methodologies, and the complete data processing lifecycle while encouraging hands-on application. Algorithms studied and implemented include logistic regression, linear regression, k-nearest neighbors, decision trees, perceptron, random forests, neural networks, k-means clustering, principal component analysis, DBSCAN, and image compression with singular value decomposition.
RELEVANT COURSES
SPRING 2025
STAT 405: R FOR DATA SCIENCE
Completing assignments and assessments centered around core components of the R programming language, as well as R's applicability to statistical and data science problems. Topics include importing data, exploring and visualizing data, applying a variety of statistical methods, and communicating results.
STAT 410: LINEAR REGRESSION
Completing labs, assignments, assessments, and projects involving linear regression and its applications. Topics include simple and multiple linear regression, least squares, analysis of variance, model selection, diagnostics, and remedial measures. The course emphasizes real-world data analysis and the implementation of statistical software.
RELEVANT COURSES
FALL 2024
DSCI 305: DATA, ETHICS, AND SOCIETY
Attended lectures, participated in group discussions, and completed assignments pertaining to the ethical implications and societal impacts of choices made by data science professionals.
DSCI 302: INTRO TO DATA SCIENCE TOOLS/MODELS
Completed labs, assignments, and quizzes focusing on data management, preparation, and modeling. Tools utilized included relational databases, pandas, and Spark. Models covered included kNearest Neighbors, linear regression, and gradient descent. The course covered Python and SQL programming languages.
SMGT 364: SPORT LAW
Acquired in-depth knowledge of the American legal system and legal practices, methods, and terminology, often with an emphasis on sports business, leadership, and operations. The course included discussions, presentations, projects, case readings, and exams.
LPAP 113: MENTAL TRAINING FOR PERFORMANCE
Learned about major psychological concepts surrounding performance-related activity, including anxiety regulation, behavior modification, goal setting, leadership and communication skills, burnout, intrinsic motivation, and self-confidence.
RELEVANT COURSES
SUMMER 2024
STAT 310: PROBABILITY AND STATISTICS
Studied a broad variety of statistical concepts, including probability, random variables, distributions of random variables, expectation, sampling distributions, estimation, confidence intervals, and hypothesis testing. Information was delivered through a series of lectures and assessed through homework assignments and three cumulative exams.
SMGT 266: LEADING WITH SERVICE
Studied industry leaders in customer service, common practices among customer service departments in the sport industry, and the unique qualities that strong employees exhibit. Covered topics such as service delivery, consumer research, and developing measurable objectives. Assignments included one reading and a series of essays, mostly centered around building a model customer service plan for a specific professional sports team to adopt based on the concepts learned in class.
RELEVANT COURSES
SPRING 2024
COMP 140: COMPUTATIONAL THINKING
Worked with one partner on in-class assignments applying Python to explain or solve real-world problems and experiments. Additionally, completed exhaustive bi-weekly projects independently.
STAT 280: ELEMENTARY APPLIED STATISTICS
Completed weekly R labs relating to lessons learned in class, including probability, descriptive statistics, probability distributions, confidence intervals, significance testing, linear regression, correlation, and association between categorized variables.
SMGT 276: SPORT MANAGEMENT PRACTICUM
Gained real-world sport management experience with 100+ internship hours, valuable guest lectures, and lessons pertaining to resumes, cover letters, interviews, portfolios, presentations, and more.
ANALYZING BASEBALL DATA WITH R (not for credit)
Attended bi-weekly meetings led by Jeff Brover, working hands-on with real baseball data in R demos. This course was affiliated with Rice Sports Analytics Team.
RELEVANT COURSES
FALL 2023
SMGT 260: INTRO TO SPORT MANAGEMENT
Gained real-world sport management knowledge with valuable guest lectures, group research presentations, and lessons pertaining to problem-solving, marketing, law, sales, event management, and agency.
DSCI 101: INTRO TO DATA SCIENCE
Acquired introductory knowledge about coding with Python, gained hands-on experience with in-class demo assignments, and worked in a large group on weekly projects, which included solving real-world data science challenges, designing a data science pipeline, and deriving valuable insights from data.
ANALYZING BASEBALL DATA WITH R (not for credit)
Attended bi-weekly meetings led by Jeff Brover, working hands-on with real baseball data in R demos. This course was affiliated with Rice Sports Analytics Team.
Selected to Fall 2023 President's Honor Roll
Rice University students, including myself (red shirt), show off our Rice pride while analyzing baseball data in the R programming language. This opportunity was presented through a bi-weekly course led by Jeff Brover of the Rice Sport Analytics Team.
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