This course introduces core algorithms, techniques and applications in generative artificial intelligence (GenAI). It covers the theory of classic generative models—such as VAEs, GANs, autoregressive transformers, and diffusion models—and their applications across text, audio, image, video, 3D and multimodal generation. Students will engage in hands-on projects (e.g., chatbots, AI art) to learn practical GenAI implementation. By the end of the course, students will master designing, implementing, and evaluating generative models and apply these techniques to solve real-life challenges.

For a student to pass the course, at least 30% of the maximum mark for the continuous assessment and 30% of the maximum mark for the examination must be obtained.