Gain a foundational understanding of Neural Networks, the building blocks of Deep Learning, including neurons, layers, and activation functions.
Explore the fundamental principles and architectures of Deep Learning models, such as feedforward networks and backpropagation, used for training neural networks.
Learn about two widely used Deep Learning frameworks - TensorFlow and PyTorch and their features for building and deploying neural network models.
Engage in a practical exercise where you will build a simple neural network using TensorFlow. Implement and train a neural network model to solve a specific problem, gaining hands-on experience in Deep Learning implementation.
Develop hands-on deep learning skills by building a Convolutional Neural Network (CNN) model to detect and classify objects in complex urban traffic environments - a core capability for autonomous vehicles (AVs).
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