IST 687 - Introduction to Data Science

Welcome to my GitHub repository for the IST 687 Introduction to Data Science course at Syracuse University. This repository serves as a portfolio of projects, homework, and key learnings from the course, which explores a variety of data science fundamentals using R.

Course Overview

IST 687 offers an applied introduction to the essentials of data science. The course covers practical aspects of data collection, processing, transformation, management, and analysis. We use R, a powerful tool for statistical analysis and data visualization, to handle real-world data and solve complex problems. The course is structured around the following key areas:

Data Management: Scripting and coding with R for effective data manipulation. Statistical Analysis: Employing R to perform descriptive and inferential statistics. Machine Learning: Exploring basic machine learning techniques within the R environment. Data Visualization: Creating insightful visualizations to interpret and communicate data findings.

Repository Structure Homework/: Contains assignments designed to reinforce the practical application of data science techniques discussed in class. Projects/: Major course projects including the final capstone project, which involve comprehensive data analysis tasks, from data cleaning to advanced modeling.

Homework Assignments: These tasks focus on specific aspects of data science, such as data cleaning, visualization, and basic modeling, to strengthen foundational skills. Capstone Project: A group project that involves analyzing a provided dataset, applying various data science methods, and presenting the findings with detailed visualizations.