Equips students with some of the most used deep learning architectures. Explore feed-forward networks, convolutional neural networks, UNETs, encoders-decoders, generative adversarial networks and transformers. Analyze tools of explainable AI. Focused on climate applications, apply these techniques to real-world data, solving problems in prediction, pattern recognition, and data-driven insights.

This course will equip students with some of the most commonly used deep learning architectures. We will explore feed-forward networks, convolutional neural networks, UNETs, encoders-decoders, generative adversarial networks and transformers. We will also analyze tools of explainable AI. Focused on environmental applications, students will apply these techniques to real-world data, solving problems in prediction, pattern recognition, and data-driven insights. Solid background in probability, statistics, and in coding (preferably Python) is recommended for enrollment in this course.

Focuses on principles & theories of law related to healthcare delivery, management & administration. Examines the application of laws on healthcare liability prevention & the risks managers face. Explores legal & ethical issues in healthcare systems; and investigates the healthcare administrator as decision-maker, leader and moral agent. Evaluates situations with potential ethical/legal implications.

An introduction to essential programming concepts, structures, and techniques. Students will gain confidence in not only reading code, but learning what it means to write good quality code. Additionally, essential and complementary topics are taught, such as testing and debugging, exception handling, and an introduction to visualization. This course is project based, consisting of a semester project and final project presentations.

Trends in hardware and software for Big Data Systems and applications. Cover principles driving data infrastructures, which enabled the training of AI models on datasets (speech, sounds, images, video, languages) and may extend to structured data (text, images, time series). AI and machine learning practitioners build and deploy data science projects on Amazon Web Services unifying data science, data engineering, and application development.

Covers the essential environments and tools for data engineering. Topics include Linux, software development and testing, database design and construction, creation and deployment of containers, and data load/transform/extraction.

An intensive overview of cloud infrastructure and their role in data science. Topics will include storage as a service, ephemeral computing resources, auto-scaling, and event-driven workloads. Special attention will be paid to cloud-native design patterns, which are built assuming the unique functionality of cloud computing resources.

Focuses on the unique integration of public health and healthcare systems. Provides students with key knowledge and skills to effectively promote health and prevent disease, while navigating public health and healthcare challenges. Emphasizes the identification of populations at risk; evidence-based care, care coordination, patient and community engagement, and reporting of outcomes. Prereq: Bachelor's Degree

Introduces students to various styles and theories of leadership. Through self-assessment and guided inquiry, students examine and create their own unique style of leadership. Students will develop approaches to adapt and modify leadership styles to various situations and individual personalities to influence organizational outcomes.

Intensive work in poetry writing, for students with prior experience. May be repeated with different instructor. For instructions on how to apply to this class, see www.engl.virginia.edu/courses. Prerequisite: Instructor permission.