Goals

Understand the core concepts and principles of deep learning.

Learn how to evaluate, fine-tune, and optimize deep learning models.

Learn the architecture and working principles of neural networks.

Gain practical skills in building and training deep learning models.

Understand the role of deep learning in various real-world applications.

Explore the ethical implications and challenges of deep learning technologies.

Introduction to Deep Learning

Defining deep learning and its relationship with machine learning.

Key differences between traditional machine learning and deep learning.

Overview of neural networks and their evolution.

The role of deep learning in modern AI applications.

Neural Networks and Architecture

Understanding neurons, layers, and activation functions.

Introduction to feedforward neural networks.

Backpropagation and gradient descent algorithms.

Deep architectures: convolutional networks (CNN), recurrent networks (RNN).

Training Deep Learning Models

Data preparation and augmentation for deep learning.

Choosing the right loss function and optimization techniques.

Hyperparameter tuning and model selection.

Using frameworks like TensorFlow and PyTorch for model development.

Applications of Deep Learning

Deep learning in image recognition and natural language processing.

Applications in speech recognition, robotics, and healthcare.

Understanding the significance of transfer learning.

Case studies and industry use cases.

Evaluating and Optimizing Deep Learning Models

Common evaluation metrics for deep learning models.

Techniques for avoiding overfitting (regularization, dropout).

Model performance enhancement techniques.

Scaling deep learning models for production.

Ethics and Challenges in Deep Learning

Ethical considerations in AI and deep learning.

Addressing bias and fairness in deep learning models.

The challenge of explainability in complex neural networks.

Regulatory and societal implications of deep learning technologies.

Certificate

Upon full attendance of this training course, participants will receive an accredited certificate issued by Al Manhal Institute, which is licensed by the Abu Dhabi Center for Technical and Vocational Education and Training. This certificate is regionally recognized, providing holders with a competitive advantage both within their organizations and when seeking new career opportunities.

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Fundamentals of Deep Learning

Goals

Contents

Introduction to Deep Learning

Neural Networks and Architecture

Training Deep Learning Models

Applications of Deep Learning

Evaluating and Optimizing Deep Learning Models

Ethics and Challenges in Deep Learning

Certificate

Certificate

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Introduction to Deep Learning

Neural Networks and Architecture

Training Deep Learning Models

Applications of Deep Learning

Evaluating and Optimizing Deep Learning Models

Ethics and Challenges in Deep Learning