Engineering in Computer Science and Artificial Intelligence

General Objectives At the end of the course, students will have a solid understanding and practical ability in the field of Generative AI, essential for tackling and solving complex problems in generative artificial intelligence. Specific Objectives Knowledge and Understanding: Acquire an in-depth understanding of the principles behind image and text generation. Learn the structures and mechanisms of generative models based on diffusion techniques and autoregressive techniques. Critical Thinking and Judgment Skills: Critically evaluate the performance of generative AI models and how they are used in real-world scenarios. Analyze the challenges related to robustness in generative AI models and develop effective solutions. Communication Skills: Present and discuss the results of generative AI projects, demonstrating proficiency in the use of advanced tools such as Diffusion Models and Transformers. Learning Skills: Experiment with emerging technologies in the field of deep learning, such as LLMs, Vision LMs, Diffusion Models, Flow-based Models, etc. Apply theoretical knowledge in practical projects to tackle real-world problems.