Human-computer interaction

This course is designed to impart comprehensive knowledge and understanding of the principles and practices underpinning the design and evaluation of usable Artificial Intelligence Systems. The curriculum is structured around the following key objectives:

- Theoretical Foundations: To familiarize students with the core models and theoretical frameworks that inform the design of effective, efficient, and user-friendly AI systems. This includes an exploration of human-computer interaction (HCI) principles and design methodologies specific to AI applications.

- Practical Tools and Techniques: To equip students with the practical tools and techniques necessary for the design and evaluation of AI systems. This includes hands-on experience with usability testing methods, and evaluation metrics to assess the user experience of AI systems.

- Real-world Application: To enable students to apply theoretical knowledge and practical skills in real-world scenarios, thereby understanding the complexities and challenges of implementing AI solutions that meet user needs and preferences.

- Problem-solving Skills: To develop students' ability to critically analyze and solve design and usability problems in AI systems, leveraging their knowledge of user-centered design principles.

- Autonomous Learning and Adaptation: To cultivate a capacity for independent learning, encouraging students to stay informed of the latest developments and trends in HCI, AI technologies, and related fields, thus preparing them for continued professional growth and adaptation to new challenges.

Upon successful completion of the course, students will:
- Demonstrate Comprehensive Knowledge: Have a solid understanding of the fundamental concepts, models, and frameworks in HCI and human-AI interaction, enabling them to design AI systems that are user-centric.
- Apply Design and Evaluation Skills: Possess the ability to effectively apply design principles and evaluation techniques to create AI systems that are effective, efficient, and easy to use.
- Solve Real-world Problems: Show proficiency in applying theoretical knowledge and practical skills to address real-world challenges, demonstrating creativity and innovation in the design of user-centered AI solutions.
- Exhibit Critical Analysis: Be capable of conducting thorough analysis and critique of AI systems, identifying usability issues, and proposing evidence-based improvements.
- Engage in Lifelong Learning: Display an ongoing commitment to learning and professional development, with the ability to autonomously explore new trends and advancements in HCI, AI, and related disciplines.
- Communicate Effectively: Demonstrate the ability to clearly and persuasively communicate design concepts, evaluation results, and recommendations to diverse audiences, including technical and non-technical stakeholders.