Abstract:

Currently, artificial intelligence is a trendy, even fashionable, topic. The method of using and developing artificial intelligence technology is widely discussed in scientific, business, political, and social aspects.

All this means that more and more people want to learn about artificial intelligence technologies, and thanks to the growing interest in the industrial environment, the demand for employees who know technologies related to machine learning is increasing.

The article is intended to familiarize the reader with the tools, development, learning, and certification paths in learning how to use and understand the operation of artificial intelligence mechanisms, using the example of Amazon's cloud environment, i.e., Amazon Web Services.

Accessible solutions from Amazon will be presented, supporting the entire process of learning, which ultimately leads to the possibility of obtaining the globally valued AWS Certified Machine Learning path.

This article focuses on Amazon SageMaker, a fully managed service that combines a broad set of tools to enable efficient and affordable Machine Learning for any use case. With SageMaker, it is possible to build, train, and deploy machine learning models at scale using tools like notebooks, debuggers, profilers, pipelines, MLOps, and more – all in one Integrated Development Environment (IDE).

The article also discusses other tools such as Comprehend, Lex, Polly, Rekognition, Textract, Transcribe, and Translate, which create complementary environments with the SageMaker mentioned above.

Keywords:

Artificial Intelligence, Machine Learning, SageMaker, Self-Learning, e-learning, AWS, Amazon Web Services, Cloud Environment.