This Institute covers the essential basis for doing data science as practiced in the 21st century. Data scientists are expected to know how to obtain relevant data for a specific problem, clean and explore data, create models using data, state inferences, make reliable predictions, and communicate findings to multiple, possibly non-technical, audiences. We will cover each of these steps in seven intense working days.
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Instructor: Ryan Moore, Associate Professor, Department of Government
Course schedule: January 4-11, 2023; 9 am to 5 pm every day
Course number: SPA-020/SPA-420/SPA-620
Participants will receive a certificate of completion.
Registration for AU Students
AU students can register for the Data Science Institute as a regular course. Talk with your adviser about registering for SPA-420 (undergraduate) or SPA-620 (graduate). This course awards 4 credit hours, and is part of the academic Spring semester.
Registration for Professionals & Visiting Students
All visiting students (new to AU), enrolled for credit or not-for-credit register for the class through AU Central. The non-credit course option is SPA-020. A visiting student fills out the course registration form and submits the form directly to AU Central. Tuition payment is due during registration. Instructions to register will be sent upon acceptance of your application.
The Institute is not open to registration through the Consortium of DC area schools. Interested students from local area schools can register for the class as a visiting student through AU Central. If taking the class for course credit, they would have to make arrangements to transfer the course credit back to their home school.
Frequently Asked Questions
The prerequisite is a basic statistics 101 class or equivalent knowledge. Some previous knowledge of R is useful but not required.
We will use R and Python at a fairly basic level for the most part, with some advanced usage carefully explained as if participants have not seen it before.
Yes, there will be a hands-on group project with real data.
Decisions are made on a rolling basis, and are currently being accepted. Non-AU students have the same preference as AU students.