
Tamara Horne
Adjunct Professor

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About me
Data Scientist | Python | SQL | Tableau | Data Analytics | Data Cleaning, Modeling, Visualization
Education

Springboard
2022 - 2023Data ScienceSpringboard Data Science Career Track, CertificationDescription : 550+ hours of hands-on course material, with 1:1 industry expert mentoroversight, and completion of 2 in-depth capstone projects. Mastered skills in Python,SQL, data wrangling, data visualization, hypothesis testing, and machine learning.

California State University, Fullerton
-Master of Music Music Performance
Experience

California Baptist University
Jan 2005 - Jan 2008Adjunct ProfessorTeaching voice to both music majors and non-majors.

First Baptist Church of Corona
Jan 2008 - Jan 2011Minister of MusicLeading an adult choir and praise team; conducting and singing for services, baptisms, and special events.

Bethlehem United Methodist Church Preschool
Jan 2014 - Jan 2019Music Teacher
Williamson County Schools
Aug 2019 - nowSIS Specialist (Data Analyst)
Aug 2023 - nowSubstitute Teacher
Aug 2022 - Aug 2023Teacher Assistant
Aug 2019 - Aug 2022

Springboard
Sept 2022 - Jul 2023Data Science FellowSpringboard Data Science Career Track - StudentDescription: 550+ hours of hands-on course material, with 1:1 industry expert mentoroversight, and completion of 2 in-depth capstone projects. Mastered skills in Python,SQL, data analysis, data visualization, hypothesis testing, and machine learning.Predicting Public Transportation Safety Risk: Predicting the safety risk implications of adding a new mode of transportation versus increasing service to current modes of transportation in Nashville, TN. Project explores three different aggregations and four regression models: linear regression, random forest, knn, and XGBoost. Results suggest Nashville should not add light rail. Instead, Nashville should consider adding service to an existing mode, the best choice of which would be commuter rail.Github: https://github.com/tamarahorne/Springboard/tree/main/Capstone%20Project%202Cancer Gene Expression Classification: Imbalanced multi-class classification problem seeking to predict type of cancer based on gene expression data. Utilizing PCA for feature reduction, both linear and non-linear models with parameter tuning, GridSearch, and cross-validation with StratifiedKFold where appropriate. Project is in progress. Show less
Licenses & Certifications
- View certificate

Excel: Power Query (Get & Transform)
LinkedInSept 2024 - View certificate

Introduction to Spark SQL and DataFrames
LinkedInJun 2023 - View certificate

Python Statistics Essential Training
LinkedInDec 2022
Volunteer Experience
Choir Director
Issued by Grassland Middle School on Aug 2022
Associated with Tamara Horne
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