CSCI-B 659 Topics in Artificial Intelligence
3 credits
- Prerequisite(s): None
- Delivery: On-Campus
Description
Special topics in artificial intelligence. This course covers recent advances in artificial intelligence. While engaging in research, students investigate advanced AI concepts such as autonomous systems, computer vision, deep learning, explainable AI, generative adversarial networks, human–robot interaction, natural language processing, quantum machine learning, and virtual assistants.
Learning Outcomes
- Assess critically theories, algorithms, and techniques within AI subfields. CS 4
- Develop sophisticated applications by applying AI methodologies, frameworks, and tools to solve complex real-world problems. CS 2
- Integrate and synthesize knowledge from different AI subfields to create comprehensive AI solutions that address multifaceted challenges. CS 4
- Demonstrate adaptability and awareness of the rapidly evolving AI landscape, keeping abreast of new developments and incorporating emerging trends into AI projects and research. CS 4
- Formulate research questions, design experiments, and conduct independent investigations exploring novel AI approaches and contribute to advancing AI knowledge. CS 7
- Present research findings, project outcomes, and AI concepts effectively through written reports, presentations, and discussions tailored to technical and non-technical audiences. CS 7
- Evaluate AI applications’ ethical considerations and societal impact, and propose responsible AI development and deployment strategies. CS 6
Policies and Procedures
Please be aware of the following linked policies and procedures. Note that in individual courses instructors will have stipulations specific to their course.