Data Exploration and Visualization

Catalog description

In this project-based Python data science course, students will explore the Python language and its use in data analysis. Students will gain hands-on experience applying statistical methods through exploratory data analysis, data wrangling, and data visualization with libraries such as pandas and the NumPy library. The course covers preparing datasets, handling missing values, and using NumPy arrays to support effective analysis. Students will also examine machine learning models such as regression models and practice model evaluation on real datasets. In addition, students will work with relational databases using SQL and explore NoSQL systems to compare different approaches to managing data. Through interactive exercises and Python projects in environments like Jupyter Notebook, students will write Python code, create visualizations, and develop essential data analytics skills for solving real world problems in data science. (Prerequisites: ENTD150, ENTD220, and INFO222)