Affective Artificial Intelligence (AI) is an emerging discipline at the intersection of computer science, psychology, and human–computer interaction. Unlike traditional systems that focus only on data and logic, affective AI emphasizes the emotional dimension of human experience. It aims to build machines capable of detecting, interpreting, and responding intelligently to human emotions. This ability transforms interactions with technology, making them more natural, intuitive, and human-centered, with applications already impacting healthcare, education, customer service, and entertainment.

The course is structured to provide clarity and depth across four main topics. You will first explore the foundations of affective AI, including its historical development, differences between cognitive and affective intelligence, and the challenges of replicating emotions in machines. Next, you will study techniques for emotion recognition, such as facial expression analysis, speech and voice recognition, sentiment analysis in text, and multimodal systems. These methods rely on algorithms, neural networks, and datasets, while facing challenges like cultural variability and bias.

Finally, the course focuses on designing and applying emotion-aware AI systems, with real-world examples like chatbots, social robots, and educational assistants. You will analyze how these systems adapt to user emotions, balance empathy with performance, and enhance engagement. Ethical concerns such as privacy, manipulation risks, and cultural perspectives are also addressed, alongside emerging regulations. By completing the course, you will gain both theoretical and practical knowledge, equipping you to evaluate, design, and responsibly apply affective AI in careers where innovation and empathy intersect.