---
title: "Data Science Learned from BYU-I"
author: "Brigham Eaquinto"
date: "July 2022"
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### Tools Learned
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- Coding Languages
- R
- Python
- SQL
- DAX
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- IDEs
- VSCode
- RStudio
- DataBricks
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- R
- Tidyverse (Dplyr, Ggplot2)
- [stats](https://stat.ethz.ch/R-manual/R-devel/library/stats/html/00Index.html) ([Saunder's Notebook](https://byuistats.github.io/Statistics-Notebook/))
- OfficeR
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- Python
- [Pyspark & Spark SQL](python_packages\spark\pyspark_notes.html)
- [Tensorflow & Keras](python_packages\tensorflow_keras_notes.html)
- [Sklearn](python_packages\sklearn_notes.html)
- [Pandas](python_packages\pandas_notes.html)
- [Numpy](python_packages\numpy_notes.html)
- [Seaborn](python_packages\seaborn_notes.html)
- [Plotnine](python_packages\plotnine_notes.html)
- [Spacy](python_packages\spacy_notes.html)
- [Gensim](python_packages\gensim_notes.html)
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- Reporting Tools:
- [QMD](qmd/qmd_notes.html)
- Streamlit Dashboard
- Power BI Reports
- __Others__
- IDAS
- Pathway Internship
- DSS
# Curriculum
### Noteable Data Science Classes
- CIT 111 Introduction to Databases
- CIT 225 Database Design & Development
- DS 250 Data Science Programming
- DS 350 Data Wrangling and Visualization
- DS 460 Big Data Programming & Analytics
- DS 498R Internship
- DS 499 Senior Project in Data Science
- MATH 325 Intermediate Statistics
- MATH 425 Applied Linear Regression
- MATH 488 Statistical and Data Science Consulting
- CSE 450 Machine Learning
- BA 315 Business Analytics
### Notable Math Classes
- MATH 112X Calculus 1
- MATH 215 Multivariable Calculus
- MATH 316 Differential Equations and Linear Algebra
- MATH 341 Linear Algebra
- MATH 423 Probability and Statistics