Learn Python remotely in four days

Python is a premier language for modern data science and data analysis and is rapidly becoming the preferred language of data scientists in both industry and academia. With Python, researchers can store and analyze data sets both large and small, collect data using APIs, create stunning data visualization, process text analysis, conduct machine learning, and so much more.

This seminar offers both a thorough introduction and an intermediate lesson on Python.

Python for Data Analysis taught by Jason Anastasopoulos, Ph.D. May 26-29, 2020

By the end of this seminar, you will be able to:

Program using Python (Jupyter) notebooks and IDEs.
Understand and use basic data analysis and visualization libraries such as NumPy, Pandas, Matplotlib, SciPy and statsmodels, among others.
Use basic data structures needed to do data analysis: variables, lists, loops, dictionaries, Boolean operators, functions.
Perform data analysis and basic statistical inference: GLMs, ANOVA, hypothesis testing.
Produce beautiful data visualizations.
Scrape and parse semi-structured data, including HTML, XML, and JSON.
Create and extract information from databases with Python.
Grasp the basics of unstructured data and natural language processing.

This is a hands-on class that will involve daily structured exercises.

How It Works

Over four days, participants will join the course via Zoom to participate in lectures, receive hands-on exercise assignments, and interact with the instructor. Although we recommend joining the seminar live, participants also have the option to take the course asynchronously by viewing the lecture videos at your convenience. Each day will follow this schedule:

11:00am-2:00pm EST: Live lecture via Zoom

After 2:00pm EST: Exercise assignment to be completed on your own

8:00pm-9:00pm EST: Live “office hour” via Zoom to review exercises and ask questions

*We understand that scheduling is difficult during this unpredictable time. If you prefer, you may take all or part of the course asynchronously. The video recordings will be available for 3 weeks after the course ends, meaning that you will get all of the class discussion and exercise solutions even if you cannot participate synchronously.

Who is Jason Anastasopoulos?

Jason Anastasopoulos, Ph.D., is an Assistant Professor in the Department of Public Administration and Policy, the Department of Political Science and the Institute for Artificial Intelligence at the University of Georgia. He has done extensive applied and theoretical work in machine learning and causal inference, and he has also worked as a machine learning scientist in the Python and R languages for governments and research organizations.

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