For students advanced beyond the level of ENCW 2600. Involves workshop of student work, craft discussions, and relevant reading. May be repeated with different instructor. For instructions on how to apply to this class or more details, please visit our program website at creativewriting.virginia.edu/ugrad.

The course is designed to not only teach students tools necessary to visualize data but also effective techniques for explaining data driven results with an emphasis on communicating statistical output in a manner that best represents the findings. Examples might include tailoring messages based on the audience or shaping visualizations to follow a story-line. Content on the development of interactive plots and dashboards will also be included.

This poetics seminar, designed for students in the English Department's Area Program in Poetry Writing but open to other students on a space-available basis, is a close readings course for serious makers and readers of poems. Seminar topics vary by semester. For more details on this class, please visit the department website at creativewriting.virginia.edu/ugrad.

Geography matters! We'll explore theories & cases to better understand issues as the struggle over the ocean/other public commons, the role of sacred spaces in Indigenous communities, how migrants make a place for themselves in their new homes, economic resilience and how capital, goods and people circulate in the economy, and more. This is a good introduction to themes raised in Global Studies.

This course covers the practice of data science practice, including communication, exploratory data analysis, and visualization. Also covered are the selection of algorithms to suit the problem to be solved, user needs, and data. Case studies will explore the impact of data science across different domains.

Exposes students to the emerging field of Data Science, its domain areas, and popular applications. Topics include analytical methods, ethical issues associated with the field, engineering, and systems necessary to support data-related work, and design principles commonly seen in data communications and human center design. Students learn from leaders in the field through a series of guest lectures and work through discussion examples.

Will expose student to fundamental coding languages in data science. Python and R will be the primary focus of the course. Popular packages such as pandas and tidyverse will be covered in depth. Additionally, project management skills such as Git and Github will be covered.

Will center on exposing students to contemporary pipelines for data analysis through a series of steadily escalating use cases. The course will begin with simple local database construction such as SQLite and foundation knowledge in terms of computational environments. The content will lay the groundwork for more advanced Systems Domain courses in the major.

Learning tools and concepts for computing on big data. Learn how to use Spark for large-scale analytics and machine learning. Spark is an open-source, general-purpose computing framework that is scalable and blazingly fast. Fundamental data types and concepts will be covered (e.g., resilient distributed datasets, DataFrames) along with Tools for data processing, storage, and retrieval, including Amazon Web Services (AWS).

This course introduces students to key business topics relevant to high technology companies. Students will learn how to understand and interpret financial statements and frame financial decisions, including building a business case. The course will explore typical organizational structures and the roles of business functions. Students will be introduced to business models and other concepts in marketing and business strategy.