📚 Overview

The Master of Professional Studies (MPS) in Data Analytics at Penn State University is a graduate program designed to develop technical, analytical, and decision-making skills for managing and interpreting complex data. Offered through Penn State’s World Campus and the College of IST, the program emphasizes real-world applications across industries.

🔍 Program Highlights

• Interdisciplinary Curriculum – Covers data science, machine learning, databases, data visualization, and decision analytics
• Hands-on Experience – Projects, case studies, and a capstone simulation
• Industry-Ready Skills – Python, SQL, Tableau, cloud computing, predictive modeling, and data mining
• Capstone Project – Integration of learned concepts into a real-world business solution

This repository showcases coursework and projects completed throughout the program, covering data collection, databases, predictive analytics, and decision-making.

📘 Course Highlights & Projects

DAAN 822: Data Collection and Cleaning

Topics Covered:

• Web scraping, APIs, data automation
• Data wrangling and transformation
• Handling missing or incomplete data

Projects:

• Web Scraping Financial Data
• Survey Data Cleaning & Transformation

DAAN 825: Large-Scale Databases and Warehouses

Topics Covered:

• SQL and RDBMS concepts
• ETL pipelines
• Database performance optimization

Projects:

• Relational Database Design
• Retail Data Warehouse

DAAN 881: Data-Driven Decision Making

Topics Covered:

• Business decision frameworks
• Predictive modeling and scenario analysis

Projects:

• Business Decision Predictive Model
• Scenario-Based Simulation

IE 575: Foundations of Predictive Analytics

Topics Covered:

• Regression, classification, clustering
• Feature engineering
• Model evaluation

Projects:

• Customer Churn Prediction
• Medical Data Classification

INSC 521: Database Design Concepts

Topics Covered:

• ER modeling and normalization
• Schema design
• Advanced SQL queries

Projects:

• Hospital ER Model
• Query Optimization on Large Dataset

SWENG 545: Data Mining

Topics Covered:

• Association rule mining
• Text and web mining
• Outlier detection and clustering

Projects:

• Market Basket Analysis
• Social Media Sentiment Analysis

DAAN 862: Analytics Programming in Python

Topics Covered:

• pandas, NumPy, scikit-learn
• Data manipulation and modeling workflows

Projects:

• Predictive Modeling in Python
• Feature Engineering for Kaggle Dataset

DAAN 871: Data Visualization

Topics Covered:

• Data storytelling and dashboard design
• Tools: Tableau, matplotlib, seaborn

Projects:

• Business KPI Interactive Dashboard
• Economic Indicator Visualizations

DAAN 888: Analytics Design and Implementation (Capstone)

Topics Covered:

• End-to-end analytics lifecycle
• Agile project development and deployment

Capstone:

• Real-World Business Analytics Solution

📁 Repository Structure

MPS-DataAnalytics/
├── DAAN_822/
├── DAAN_825/
├── DAAN_881/
├── IE_575/
├── INSC_521/
├── SWENG_545/
├── DAAN_862/
├── DAAN_871/
└── DAAN_888/

⚙️ Technologies Used

• Python: pandas, NumPy, scikit-learn, BeautifulSoup, requests
• SQL: PostgreSQL / MySQL
• ETL Tools & Frameworks
• Jupyter Notebooks
• Tableau, matplotlib, seaborn

📬 Contact

For questions or collaborations:
📧 jeniffer.soto1@gmail.com

🧠 About the Author

Jeniffer Soto Perez
Master of Professional Studies in Data Analytics
Penn State University, 2025