Deep Learning on AWS
Duration : 1 Day (8 Hours)
Deep Learning on AWS Course Overview:
The Deep Learning on AWS course provides comprehensive training on AWS’s deep learning solutions. Throughout the course, participants will gain knowledge about the scenarios in which deep learning is applicable and understand the underlying principles of deep learning.
Participants will learn how to leverage Amazon SageMaker, a fully managed machine learning service, and the MXNet framework to run deep learning models on the cloud. The course covers the process of training and deploying deep learning models using these tools.
Additionally, participants will learn how to deploy their trained deep learning models using services like AWS Lambda. They will explore the design and implementation of intelligent systems on AWS, utilizing the capabilities of deep learning.
By the end of the course, participants will have a solid understanding of AWS’s deep learning solutions, the use cases where deep learning is beneficial, and the practical implementation of deep learning models on AWS. They will be equipped with the knowledge and skills to run, deploy, and design intelligent systems using deep learning technologies.
Course level: Intermediate
Intended audience
This course is intended for:
- Developers who are responsible for developing deep learning applications
- Developers who want to understand the concepts behind deep learning and how to implement a deep learning solution on AWS Cloud.
Module 1: Machine learning overview
- A brief history of AI, ML, and DL
- The business importance of ML
- Common challenges in ML
- Different types of ML problems and tasks
- AI on AWS
Module 2: Introduction to DL
- Introduction to DL
- The DL concepts
- A summary of how to train DL models on AWS
- Introduction to Amazon SageMaker
- Hands-on lab: Spinning up an Amazon SageMaker notebook instance and running a multilayer perceptron neural network model
Module 3: Introduction to Apache MXNet
- The motivation for and benefits of using MXNet and Gluon
- Important terms and APIs used in MXNet
- Convolutional neural networks (CNN) architecture
- Hands-on lab: Training a CNN on a CIFAR-10 dataset
Module 4: ML and DL architectures on AWS
- AWS services for deploying DL models (AWS Lambda, AWS IoT Greengrass, Amazon ECS, AWS Elastic Beanstalk)
- Introduction to AWS AI services that are based on DL (Amazon Polly, Amazon Lex, Amazon Rekognition)
- Hands-on lab: Deploying a trained model for prediction on AWS Lambda
We recommend that attendees of this Deep Learning on AWS course have:
- A basic understanding of ML processes
- Knowledge of AWS core services like Amazon EC2 and AWS SDK
- Knowledge of a scripting language like Python
Q: What is Deep Learning on AWS training?
A: This training is a comprehensive program designed to provide individuals with the knowledge and skills needed to build and deploy DL models using Amazon Web Services (AWS). It covers various aspects of deep learning, including neural networks, model training, deployment, and optimization using AWS services such as Amazon SageMaker, AWS DeepLens, and AWS DeepRacer.
Q: Who should consider taking training?
A: This training is suitable for data scientists, machine learning engineers, software developers, and anyone interested in DL techniques and applications on the AWS platform. It is beneficial for those who want to enhance their understanding of DL concepts and gain hands-on experience with AWS services for building and deploying DL models.
Q: What topics are covered in this training?
A: The training covers a range of topics, including deep learning fundamentals, neural networks and architectures, model training and optimization, computer vision and natural language processing with deep learning, deploying models on AWS infrastructure, and best practices for deep learning on AWS.
Q: Are there any prerequisites for taking this training?
A:
We recommend that attendees of this course have:
- A basic understanding of ML processes
- Knowledge of AWS core services like Amazon EC2 and AWS SDK
- Knowledge of a scripting language like Python
Q: How can I prepare for this training?
A: To prepare for the training, it is recommended to have a good understanding of machine learning concepts, Python programming, and deep learning frameworks. Familiarizing yourself with AWS services like Amazon SageMaker, AWS DeepLens, and AWS DeepRacer will also be beneficial. Exploring relevant online resources, tutorials, and documentation can further enhance your preparation.
Q: Is Deep Learning on AWS training available online?
A: Yes, We offer online training options for this training to provide flexibility for learners.
Q: Can Deep Learning on AWS training help in obtaining AWS certifications?
A: While this training provides valuable knowledge and skills in deep learning techniques on the AWS platform, it does not directly prepare you for specific AWS certifications. However, it lays a solid foundation for pursuing advanced certifications related to machine learning or AWS architecture.
Choose Learning Modality
Discover the perfect fit for your learning journey
Live Online
- Convenience
- Cost-effective
- Self-paced learning
- Scalability
Classroom
- Interaction and collaboration
- Networking opportunities
- Real-time feedback
- Personal attention
Onsite
- Familiar environment
- Confidentiality
- Team building
- Immediate application
