Earning Criteria

• Complete DATA 2123 Data Visualization
• Course provides a comprehensive introduction to data visualization using Python, focusing on 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 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. Course covers a variety visualization technique 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.
• 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 work using platforms like GitHub and Jupyter Notebooks.
• Skills: 1) Python Coding for Pictures: You will learn to use special tools like Matplotlib and Seaborn to turn boring numbers into colorful charts and graphs. 2) Cleaning Data: You will learn how to use Pandas to fix messy data so that your charts are accurate and don't have as many errors. 3) Making Interactive Dashboards: You will learn how to build apps where people can click and move things around to see different parts of the data.
• Coding with Others: Students will learn how to use GitHub and Jupyter Notebooks to share your work and finish projects with your teammates.
• Data Storytelling: Students will be able to look at data and explain what it means in a clear way that anyone can understand.
• Picking the Right Chart: Students will know how to choose the best kind of graph for different jobs, like showing how things change over time or comparing different groups.
• Professional Problem Solving: Students will be able to take real-life problems and use your computer skills to find and show the answers.
• Designing for Users: Students will understand how to make charts that are not just pretty but are easy for people to read and use to make decisions.