The course is focused on an exploring the dynamics of teams and leadership within the complexities and structures of the organizations in which students work in professional practice internships. The course combines organizational behavior with concepts of teams and organizations.

Students apply academic experiences in professional and/or research settings; reflect and critically and constructively analyze experiences from multiple perspectives; and view the work as connecting course content authentic contexts. Students work as professionals with site supervisors and instructors to complete related assignments and relevant background research on the professional and academic resources available.

An Independent Study in Archaeology. Subject to be determined by student and instructor.

The data science project course will allow students to take the knowledge gained in each of the four required courses and apply them to a data driven problem. Students will work in groups and can either choose a project provided by SDS faculty or can propose a project for approval. Upon completion of the course students will be required to present their results and publish project content to an open forum.

Principles of interactivity in application and dashboard development using R, Python, and JavaScript programming languages. Design visually appealing and user-friendly interfaces, develop interactive applications for data visualization, and build dynamic dashboards for effective data communication with end-users. Covers theoretical concepts and hands-on implementation to provide a comprehensive understanding of the full design process.

Explainable artificial intelligence (XAI) is a subfield of machine learning that provides transparency for complex models to connect the technical meaning to social interpretation. Explore interpretability, transparency, and black-box machine learning methods. Covers definitions, decision support, trust, and ethical considerations, and the latest advances in creating reliable and transparent AI models.

Understand Deep Learning covering neural networks, activation functions, and optimization algorithms. Gain experience with TensorFlow and PyTorch, mastering key techniques such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Adversarial Networks (GANs). Explore transfer learning, reinforcement learning, and natural language processing (NLP), along with industry applications and ethical considerations.

In this course, students gain experience applying global perspectives, as well as research methods and techniques, to one of several real-world issues. Team-taught, the course allows students to choose a path that includes a methodological foundation, a deep dive into a particular method, a chance to practice a useful skills related to Global Studies professions, and culminating in the applied research project.

LPPL 4225 is designed to foster three critical skillsets:  1) The expansion of your self-awareness to enhance your competence as a leader, 2) Learning ways to support and inspire the development of strengths in others, and 3) Combining these skills to improve the effectiveness of your student organizations at UVA by reflecting on the organizational and interpersonal dynamics of those groups.

This class provides a general overview of film production in Brazil since 1990. We will screen and discuss a variety of documentary and feature-length fiction films, paying special attention to their formal construction and respective portrayals of Brazilian society, particularly as they unfold in a context increasingly marked by globalization and neoliberalism.