Learning Deep Learning: Unit 3

Coursera MOOC / Non-credit USD 49
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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'll learn

  • understand key deep learning architectures
  • build models for text and image data
  • apply deep learning techniques for multitask learning
  • implement ethical considerations in AI

Course objectives

  • develop skills in TensorFlow and PyTorch
  • execute deep learning projects in real-world contexts
  • enhance understanding of model tuning and deployment

Skills you'll gain

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