Python programming skills are essential for working with, analyzing, and deriving insights from environmental data. In this intensive EDS 217 course, students will develop fundamental skills in Python programming with a focus on environmental data science applications. Topics covered include basic Python syntax, data structures, functions, libraries commonly used in data science (e.g., pandas, numpy, matplotlib, seaborn), and introductory data analysis and visualization techniques.
The goal of EDS 217 (Essentials of Python for Environmental Data Science) is to prepare incoming MEDS students with the Python programming skills required for their data science courses and projects in the program. By the end of the course, students should be able to:
- Write, interpret, and debug Python code for data manipulation and analysis
- Utilize key Python libraries for environmental data science (e.g., pandas, numpy, seaborn, matplotlib)
- Perform basic data analysis and create visualizations using Python
- Apply Python programming skills to conduct environmental data science analyses
- Collaborate with peers on coding projects and communicate results effectively
- Understand best practices in Python programming and project organization
Visit the course page on the Bren Website.
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EDS 217 builds upon the foundations laid by numerous other introductory python programming courses and the overall course design of other MEDS classes. We would like to acknowledge the contributions of former students and colleagues whose materials and insights have helped shape this course.