Data Understanding and Visualization

The University of Colorado Boulder, situated against the stunning backdrop of the Rocky Mountains, is a flagship institution renowned for its academic excellence, research prowess, and vibrant campus life. CU Boulder has evolved into a hub of innovation and intellectual exploration. The university offers a diverse range of undergraduate, graduate, and professional programs across various disciplines, encouraging students to pursue their passions and make meaningful contributions to society. At CU Boulder, students engage with world-class faculty who are leaders in their fields, fostering an environment that promotes critical thinking and creativity. The campus is a melting pot of ideas and cultures, providing a rich tapestry of experiences for students. With a commitment to sustainability and a focus on cutting-edge research, the University of Colorado Boulder continues to be a beacon of higher education, preparing students to navigate the complexities of our ever-changing world.

The "Data Understanding and Visualization" course provides students with essential statistical concepts to comprehend and analyze datasets effectively. Participants will learn about central tendency, variation, location, correlation, and other fundamental statistical measures. Additionally, the course introduces data visualization techniques using Pandas, Matplotlib, and Seaborn packages, enabling students to present data visually with appropriate plots for accurate and efficient communication.Learning Objectives:1. Understand and communicate the various aspects of statistics of datasets, including measures of central tendency, variation, location, and correlation.2. Gain insights into basic statistical concepts and use them to describe dataset characteristics effectively.3. Utilize Pandas for data manipulation and preparation to set the foundation for data visualization.4. Master the utilization of Matplotlib and Seaborn to create accurate and meaningful data visualizations.5. Choose appropriate plot types for different data types and research questions to enhance data comprehension and communication.Throughout the course, students will actively engage in practical exercises and projects, enabling them to explore statistical concepts, conduct data analysis, and effectively communicate insights through compelling visualizations.