DATA 2123 — DATA VISUALIZATION
This course provides a comprehensive introduction to data visualization using Python, focusing on the principles and techniques necessary to create clear, accurate, and aesthetically pleasing visual representations of data. Students will gain hands-on experience with popular Python libraries such as Matplotlib, Seaborn, Plotly, and Bokeh, learning to create both static and interactive visualizations. Throughout the course, students will develop skills in data preparation and cleaning using Pandas and NumPy, ensuring that their visualizations are based on accurate and meaningful data. The course will cover a variety visualization techniques for different data types, including categorical, numerical, and time-series data. Students will also learn to design interactive dashboards using tools like Dash and Streamlit, enhancing their ability to present data in an engaging and user-friendly manner. Emphasis will be placed on storytelling with data, enabling students to communicate their insights effectively to diverse audiences. Real- world projects and case studies will provide practical experience, allowing students to apply their knowledge to real data scenarios. Additionally, the course will keep students updated with the latest trends and advancements in data visualization and Python libraries. By the end of the course, students will be equipped with the skills to create compelling data visualizations, analyze and interpret visual data, and collaborate with peer to share their