Course overview
Students will explore the diverse applications of generative AI and gain practical experience with using contemporary generative models. This is an advanced course for the purposes of ACS accreditation. This course aims to provide students with a comprehensive and advanced understanding of generative artificial intelligence, focusing on its theoretical foundation and real-world applications. In this course, students will explore the core principles of generative models, including but not limited to Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and diffusion models. Students will apply their advanced knowledge of generative AI on a variety of applied settings.
- Foundations Of Generative Ai
- Deep Learning Models
- Applications Of Generative Ai
Course learning outcomes
- Design, train, and fine-tune, and fine-tuning a variety of state-of-the-art generative models, including GANs, VAEs, and diffusion models
- Deploy existing generative AI solutions in a variety of settings
- Analyse and address ethical, security, and societal implications of using Generative AI
- Develop prototype solutions to real-world problems
- Analyse theoretical and complex practical problems by applying theoretical foundations of generative AI
Degree list
The following degrees include this course