Advanced AI Techniques: Deep learning and neural networks | Generative AI models
Deep Learning and Neural Networks: This course dives deep into the advanced concepts of deep learning and neural networks. You’ll explore the architecture and functioning of neural networks, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs). The course covers techniques for training deep learning models, optimizing performance, and addressing common challenges such as overfitting and vanishing gradients. You’ll gain knowledge with popular frameworks like TensorFlow and PyTorch.
Generative AI Models: Learn about the cutting-edge generative AI models that are transforming the field of artificial intelligence. This section focuses on models such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and diffusion models. You’ll understand how these models generate new data, from realistic images to creative text, by learning patterns from existing datasets. The course also covers practical applications and ethical considerations of generative AI, providing a comprehensive understanding of its capabilities and limitations
