Course on Getting Started with AWS Machine Learning [Online, 8 Hours]: Enroll Now

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About the course

Machine learning (ML) is one of the fastest growing areas in technology and a highly sought after skillset in today’s job market. The World Economic Forum states the growth of artificial intelligence (AI) could create 58 million net new jobs in the next few years, yet it’s estimated that currently there are 300,000 AI engineers worldwide, but millions are needed.

This means there is a unique and immediate opportunity for you to get started with learning the essential ML concepts that are used to build AI applications – no matter what your skill levels are. Learning the foundations of ML now, will help you keep pace with this growth, expand your skills and even help advance your career.

This course will teach you how to get started with AWS Machine Learning. Key topics include: Machine Learning on AWS, Computer Vision on AWS, and Natural Language Processing (NLP) on AWS. Each topic consists of several modules deep-diving into variety of ML concepts, AWS services as well as insights from experts to put the concepts into practice.

What you will learn?
  • Key problems that Machine Learning can address and ultimately help solve.
  • How to build intelligent applications using Amazon AI services like Amazon Comprehend, Amazon Rekognition, Amazon Translate and others.
  • How to build, train and deploy a model using Amazon SageMaker with built-in algorithms and Jupyter Notebook instance.
  • Sneak peek into AWS DeepLens – The world’s first deep learning enabled video camera for developers.
Skills you will gain?
  • Artificial Intelligence (AI)
  • Machine Learning
  • Amazon SageMaker
  • Natural Language Processing (NLP)
  • Computer Vision
Syllabus
  • Introduction to Machine Learning
  • Machine Learning Pipeline
  • Amazon AI Services: Computer Vision
  • Amazon AI Services: NLP
  • Introduction to Amazon SageMaker

To enroll in this course, click the link below.

Course on Getting Started with AWS Machine Learning

Note: Noticebard is associated with Coursera through an affiliate programme.

 

 

Disclaimer : We try to ensure that the information we post on Noticebard.com is accurate. However, despite our best efforts, some of the content may contain errors. You can trust us, but please conduct your own checks too.

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