Generative AI
Course Summary
This course provides a comprehensive introduction to Generative AI, covering the principles behind generative models, deep learning architectures, and real-world applications. Participants will explore Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer-based models (GPT, BERT, Stable Diffusion). The course will focus on applications in image generation, text synthesis, music composition, and creative AI, using Python, TensorFlow, and PyTorch.
Key Learning Outcomes
- Understand the fundamentals of Generative AI and its role in modern artificial intelligence,
- Learn how GANs and VAEs generate realistic images, text, and music.
- Implement Transformer-based models (GPT, BERT) for text generation and NLP tasks.
- Explore practical applications of generative models in content creation, drug discovery, and simulation.
- Gain hands-on experience with AI tools for image and text generation.
