Learning Deep Learning: Unit 3

About this course

This course covers key deep learning architectures such as BERT and GPT, focusing on their use in applications like chatbots and prompt tuning. You will learn how to build models that combine text and images, and generate text from visual data. The course also addresses multitask learning and computer vision tasks, including object detection and segmentation, using networks like R-CNN, U-Net, and Mask R-CNN. Topics include ethical considerations in AI and practical advice for tuning and deploying models. Through hands-on projects in TensorFlow and PyTorch, you will develop the skills needed to build, optimize, and apply deep learning solutions in real-world situations.

What you will learn

• Master large language models and transformer architectures for advanced natural language processing applications.
• Build and deploy multimodal networks that integrate multiple data types, such as text and images.
• Implement multitask learning and solve advanced computer vision problems, including object detection and segmentation.
• Apply ethical principles and practical strategies for tuning and deploying deep learning models in real-world settings.