Introduction

This course provides an in-depth understanding of deep learning, covering fundamental concepts and advanced methods used in neural networks, convolutional and recurrent neural networks (CNNs and RNNs), and generative models. Learners will explore applications in computer vision, NLP, and graph-based tasks, learning to evaluate deep learning techniques and apply them to solve real-world problems, while critically considering the limitations and ethical aspects of deep learning models.

Learning Outcomes

• Understand theoretical concepts of deep learning.
• Compare and evaluate various deep learning approaches.
• Identify limitations of deep learning.
• Apply deep learning techniques in computer vision, speech, text analysis, and graph processing.