Deep Learning on AWS

The Deep Learning on AWS course offers participants the opportunity to explore deep learning solutions and delve into the principles and use cases of this advanced machine learning technique. Throughout the course, participants will learn how to leverage Amazon SageMaker and the MXNet framework to run deep learning models efficiently in the cloud.

By enrolling in this course, you will gain valuable insights into the application of deep learning in various domains and industries. You will understand the underlying principles of deep learning and its potential for solving complex problems and making intelligent systems.

Hands-on experience is an integral part of the course, and you will learn how to utilise tools such as AWS Lambda to execute your deep learning algorithms. This practical approach will enable you to build and deploy intelligent systems on AWS while leveraging the power of deep learning.

The course provides a comprehensive understanding of using Amazon SageMaker and MXNet for training and deploying deep learning models at scale. You will learn techniques for data preparation, model training, hyperparameter optimisation and deployment.

Additionally, you will explore the integration of deep learning models with other AWS services to create end-to-end intelligent solutions.

• Developers working on Deep Learning Applications
• Developers who want to understand the concepts behind deep learning and how to implement a deep learning solution on AWS Cloud

• Basic knowledge of Machine Learning processes
• Knowledge of AWS core services like Amazon EC2 and AWS SDK
• Knowledge of a scripting language like Python

• Gain a comprehensive understanding of the core concepts and principles of deep learning and machine learning
• Recognise the key components and ecosystem of a deep learning infrastructure
• Learn to effectively use the MXNet programming framework in conjunction with Amazon SageMaker for deep learning tasks
• Explore best practices and appropriate AWS setups for optimising deep learning workflows and infrastructure
• Understand how to preprocess and prepare data for deep learning models on AWS
• Implement various deep learning architectures and models using Amazon SageMaker and MXNet
• Explore techniques for model training, hyperparameter tuning, and evaluation in the context of deep learning on AWS
• Learn how to deploy and serve deep learning models in production environments using AWS infrastructure
• Gain insights into integrating deep learning models with other AWS services for building end-to-end intelligent systems
• Develop the skills to effectively monitor, manage, and troubleshoot deep learning workflows on AWS