Deep Learning

Catalog description

Inspired by the structure and function of the human brain, deep neural networks have driven groundbreaking advancements in Computer Vision, Natural Language Processing (NLP), Reinforcement Learning, and Generative AI, making Deep Learning one of the most influential and in-demand AI technologies today. Deep Learning powers many real-world applications, including: • Facial recognition & automated image captioning • Speech recognition & virtual assistants • Search engines & personalized recommendations • Autonomous systems & robotics • Generative AI applications (e.g., AI art, chatbots, music composition, and video synthesis) This course provides a comprehensive introduction to the foundations, architectures, and practical implementations of Deep Learning. Students will explore fundamental concepts of neural networks, optimization techniques, model architectures, and real-world applications. Hands-on programming assignments and projects will equip students with the ability to develop and fine-tune deep learning models using leading frameworks such as TensorFlow, PyTorch, Keras, and Hugging Face. Additionally, students will examine the ethical and societal implications of deep learning, including bias, fairness, explainability, and adversarial robustness, gaining the knowledge to build responsible and secure AI systems.