Course overview
This is course is designed to delve into the intricacies of deep learning, focusing on cutting-edge applications and architectures. The course emphasises the practical application of deep learning techniques, particularly in handling image data using convolutional neural networks (CNNs). Students will explore a variety of deep learning frameworks and gain hands-on experience through detailed case studies that showcase the implementation of these technologies in real-world scenarios. From recognising visual patterns to enhancing image processing capabilities, the course offers a thorough examination of how deep learning can be leveraged to solve complex problems in various domains, preparing students for innovative challenges in the field of AI and ML.
- Deep Learning Foundation
- Neural Network
- Advanced Cnn Architectures
- Transformers And Their Applications
Course learning outcomes
- Comprehensive understanding of deep learning fundamentals, including activation functions, optimisation algorithms, and framework setup
- Proficiency in designing, implementing, and optimising CNNs for image processing tasks
- Advanced capability in leveraging complex CNN architectures for high-level image processing tasks such as object detection and image segmentation
- Understanding and application of transformer architectures within the context of vision-related tasks