Institute for Data Science and Big Data

January 3 - 12, 2024 | Hybrid Event

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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The course consists of a dynamic mixture of theoretical lectures, guest speakers, and group assignments. The guest lectures include data science leaders from Washington’s unparalleled mixture of government, academia, and business. Statistical topics include: exploratory methods, graphics, regression, machine learning, ensembles, clustering analysis, and Bayesian approaches. Specific technical skills including: R, Python, Pandas, JavaScript, HTML/CSS, API Interactions, Social Media Mining, SQL, Tableau, GitHub, and more.

View the course flyer.

Course Information

Instructor: Ryan Moore, Associate Professor, Department of Government
Course schedule: January 3 - 12, 2024; 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

Are there any prerequisites or knowledge of specific software programs required before attending?

The prerequisite is a basic statistics 101 class or equivalent knowledge. Some previous knowledge of R is useful but not required.

How deep the instruction will go into analysis with R and the other software packages mentioned in the course description?

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.

Will there be a lot of hands-on work conducting analysis?

Yes, there will be a hands-on group project with real data.

When will decisions about acceptance for non-AU students be made?

Decisions are made on a rolling basis, and are currently being accepted. Non-AU students have the same preference as AU students.