What is AWS Machine Learning?
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Machine Learning is a concept that has truly brought a revolution in the data-driven business scene of today. Now, predicting customer behavior and detecting fraud activities has become extremely easy, which in turn, provide valuable insights to experts well beforehand.
This has helped in creation of business strategies that are much more effective than before, making sure businesses get an edge over their competitors in the market. But ML can be conceptually pretty complex to get a grasp of. Let us first take a look at what it means and how one can have a better understanding of it.
Machine Learning – An Overview
Machine Learning (ML) is the process of training computers to recognize patterns in historical data, empowering them to make predictions on new data. These predictions serve as a foundation for informed business decisions and strategic planning.
However, becoming well-versed with ML is not the easiest task in the first place. This is often due to a lack of awareness on the resources related to the topic. Amazon Web Services (AWS) provides an efficient ecosystem for understanding all the basics of ML among a host of other cloud services. Let’s find out how exactly it helps individuals become well-versed with ML.
How Does AWS Help Achieve Machine Learning Literacy and Excellence?
There are a number of services that AWS provides, like Amazon SageMaker, which helps individuals in figuring out the process of building, training, and deploying ML models easily. Other than that, AWS also provides a series of classroom training courses to help individuals and organizations build ML expertise, which are: –
- Machine Learning Pipeline on AWS: This intermediate-level course spans four days and equips learners with fundamental ML concepts and skills. Participants learn to use an iterative ML process pipeline to solve real-world business challenges in a project-based learning environment.
- Practical Data Science with Amazon SageMaker: This course focuses on developing practical skills in data science on the AWS Cloud using Amazon SageMaker. Participants learn how to develop, train, and deploy ML models effectively, with hands-on labs and instructor-led guidance.
- MLOps Engineering on AWS: Extending the DevOps methodology to ML, this course helps organizations build and deploy ML models efficiently. Participants learn about the MLOps maturity framework, emphasizing best practices for data, model, and code management in ML deployments.
Alongside the courses, AWS additionally offers the AWS Certified Machine Learning – Specialty certification, which validates an individual’s knowledge and ability to work with ML models on AWS for focused business solutions. This certification is intended for people who perform development or data science roles and have at least one year of experience in developing, architecting or running Machine Learning/Deep Learning workloads in the AWS Cloud.
Join Hands With Cloud Wizard to Master Machine Learning on AWS
Teaming up with an Advanced Tier Training Partner can help you achieve ML expertise very conveniently. Cloud Wizard offers authorized training and certification courses for AWS. Individuals gain proficiency in various cloud-based concepts, and in turn, become employment-ready with the rigorous classroom courses, specialized exam readiness training sessions, and expert guidance provided at Cloud Wizard’s training platform.
Want to explore more cloud training courses? Check them out right here!
