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Hands-On Exercises: This is a hands-on course, with at least 50% of in-class time spent in small groups. In each 3.5-hour session, we'll have cover 2-3 topics around a central unit, working in small groups to complete exercise problems in a data science notebook. Two additional worksheet notebooks (~90-120 minutes of work) designed to flesh out the topic covered or to prepare you for the next week will need to be done outside of class time.
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Programming Platform: There are a wide variety of analysis platforms we can use to to program in Python. In this course, we will learn 4 different platforms:
- Deepnote
- VS Code Web in GitPod
- Jupyter Lab with Conda
- VS Code Desktop with Conda
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BYOD (Bring Your Own Data): On the final day of the course, we will analyze one of our own datasets. The rest of the course we will use prepared data supplied by the instructor, or generate our own (in cases of simulated data).
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All People Are the Right People, All Questions Are Good Questions, All Directions Are Good Directions: The course may go in different directions based on the interests and questions of the group. That's just fine! There is an endless amount of material for us to learn in data analysis; we'll learn as much as we can about as much as we can.
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Python's Syntax and Data Science Notebooks with DeepNote: Nov 21, 2022 09:00 AM - 12:30 PM
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Numpy Arrays and Plotting with Matplotlib: Nov 28, 2022 09:00 AM - 12:30 PM
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Multidimensional Arrays and Statistics with Scipy-Stats: Dec 5, 2022 09:00 AM - 12:30 PM
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Tabular Data Analysis with Pandas DataFrames and Seaborn Statistical Plotting: Dec 12, 2022 09:00 AM - 12:30 PM
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Batch Data Analysis: Programming a Workflow: Jan 16, 2023 09:00 AM - 12:30 PM
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Bringing it All Together: Analyzing Your Own Data On Your Own Computer: Jan 23, 2023 09:00 AM - 12:30 PM