Skills Overview

Programming Languages

• Python
• R
• R-Markdown
• SQL

R Packages

• Tidyverse, Dplyr, MASS, DT, Kable, Pander, Car

Currently Learning

• Machine Learning
• Time Series Forecasting

Tools and Technologies

Python Libraries

• Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn
  
• XGBoost, Random Forest, Statsmodels, PySpark, PyTorch

Modeling and Machine Learning

• Logistic Regression, Decision Trees, Cross-Validation
  
• Neural Networks (NN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN)
  
• Feature Engineering, Model Evaluation (RMSE, R², MAE, MSE, Confusion Matrix)

Data Analysis and Visualization

• Tableau, Excel, Quarto
  
• Jupyter Notebooks, Google Colab

Development and Version Control

• Git, GitHub, VS Code, Markdown

Databases and SQL

• MySQL, SQLite, PostgreSQL
  
• ERD Design, Data Cleaning, Joins, Set Operations

Web and Reporting

• HTML/CSS (via Quarto)
  
• GitHub Pages, Portfolio Development

Collaboration and Leadership

• Project Management
  
• Communication and Team Collaboration
  
• Leadership Experience (Digital Communications Supervisor at BYU–Idaho)

Practical Experience

Hands-on with SQL normalization, exploratory data analysis, feature engineering, and producing clean, web-ready reports using tools like Quarto and Jupyter Notebooks.

Want to see examples?
Visit the Projects page for detailed case studies and write-ups.