Deep learning has revolutionized artificial intelligence, enabling machines to perform tasks once considered exclusive to human intelligence. This seminar offers a comprehensive introduction to deep learning, emphasizing its foundational principles and practical applications in image analysis. The architectures and functionalities of neural  networks, including convolutional neural networks (CNNs), are examined in detail. Key principles and strategies for designing robust neural networks are discussed, with a focus on architectural choices, activation functions, and loss function selection. Participants will gain valuable insights into developing models that achieve high performance and generalization. The seminar also includes illustrative examples and case studies to demonstrate real-world applications.