Introduction to Deep Learning is a beginner-friendly course designed to help students understand how modern AI systems learn from data and make intelligent predictions. The course covers the core concepts, techniques, and tools used in building deep neural networks, with a balance of theory and hands-on practice.
Students will explore topics such as perceptrons, activation functions, training and optimization, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and key applications like image classification, natural language processing, and generative models. No prior experience with machine learning is required, though basic knowledge of Python is helpful.
- Teacher: Nalini Jain
