AWS recently released a new one-day advanced training course, Deep Learning on AWS, and we wanted to answer some questions about the course and provide you with additional details that extend beyond the course outline. But first…
What exactly is deep learning?
Deep learning is a subset of machine learning, which is a subset of artificial intelligence (AI). AWS further explains deep learning as allowing “computers to learn independently and undertake tasks with little supervision, promising extraordinary benefits for both science and industry.” Unlike traditional machine learning, deep learning attempts to simulate the way our brains learn and process information by creating artificial “neural networks” that can extract complicated concepts and relationships from data. Deep learning models improve through complex pattern recognition in pictures, text, sounds and other data to produce more accurate insights and predictions.
Using deep learning on the cloud will enable users to design, develop and train applications faster by leveraging distributed networks. Organizations using deep learning models can scale the models efficiently at lower costs using GPU processing power. It’s being used in business cases, such as:
- Computer vision
- Speech recognition
- Natural language processing
- Recommendation engines
AWS supports deep learning with three types of AWS Deep Learning AMIs: Condi AMI, Base AMI and AMI with source code.
The rapid advancement of deep learning is sure to continue, but as a user, are your skills advancing at the same rate? In order to maximize the use of the tools and services AWS creates, such as the AMIs, you’ll need to learn what they can do. Deep Learning on AWS will help to do just that.
What is the goal of this course?
The course aims to teach students the difference between machine and deep learning, identify concepts within the deep learning ecosystem, leverage MXNet programming framework for deep learning workloads and better understand the AWS solutions for deep learning deployments.
What will you learn?
Students will learn an introduction to machine learning, deep learning and to MXNet on AWS, plus how to deploy deep learning workloads on AWS. There are hands-on labs that will teach students how to set up deep learning AMI instances and run multilayer perceptron models, convolutional neural network models and predicting images, plus how to deploy a deep learning model for predicting images using AWS Lambda.
Who should take it?
Since developers are primarily involved and responsible for creating the learning models, this course will benefit them the most. Whether you’re responsible for developing deep learning applications or want to get a better understanding of the concepts and implementation aspects to share with your team, this course will provide essential information and tips.
How will this course impact your job?
This course will help to make your job easier by allowing you to use AWS’ deep learning tools and services more quickly and efficiently. You may even wind up as the “go-to” on your team to share the knowledge and wealth when it comes to this rapidly advancing technology. Everyone wants to be that person, right?
Does this course align with a certification?
Although this course isn’t directly aligned to a certification like most AWS courses, it will be an advanced-level course that may wind up helping if you’re looking to achieve your Big Data Specialty Certification. Other related certifications for developers include AWS Certified Developer – Associate and AWS Certified DevOps Engineer – Professional.
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