Python for Data Science and AI

July 18, 2020

Completed the IBM Python for Data Science and AI course!

IBM Python for DS and AI

Explored and worked with: Python programming basics (syntax, data types, expressions, variables, string operations, data structures, conditions, loops, functions, objects, classes). Python libraries: Pandas and Numpy using Jupyter Notebooks. Accessed and extracted web-based data by working with REST APIs using requests and performing web scraping with BeautifulSoup.

Analyze Trends and Predict College Enrollment

May 30, 2025

For my final capstone project (M.S. Advanced Data Analytics), I analyzed Fall 2023 U.S. college enrollment data (115K records, 5,900+ institutions) to uncover demographic patterns and predict graduate enrollment.

Analyze Demographic Factors and Predict College Completion

December 01, 2024

Demographic Factors and College Completion
Tools:Python (pandas, scikit-learn, matplotlib), Jupyter Notebook

Data Visualization and Communication

May 30, 2021

I recently completed the Data Visualization and Communication program and utilized spreadsheets, Python and Plotly to explore and analyze the 2019 AustinISD TEA accountability ratings as my final project!

Data Analysis and Knowledge Discovery

May 30, 2021

As my final project for the Data Analysis and Knowledge Discovery course, I created a side-by-side comparison tool to explore the 2019 ratings of any two schools or districts in Texas.

Saúl Z. Martínez

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