AWS Certified Machine Learning – Specialty | Pearson

Learn the techniques and approaches to successfully pass the AWS Certified Machine Learning – Specialty Exam with hands-on exercises.

Getting the AWS Certified Machine Learning – certification highlights your versatility as an ML engineer. Usually, ML engineers focus on handling data and building models, so if you know can use cloud tools, it makes you an even more valuable as an MLOps engineer. You’ll be able to ingest your own data, get through the feature engineering process, train and evaluate models, and deploy them to where they will be consumed. This certification shows that you know how to do full-stack ML development.

In this series of videos, author Milecia McGregor shares a mix of slides and demonstrations in AWS, along with some examples in Visual Studio with Python. It’s just what you need to learn to pass the exam. It includes an overview of concepts with hands-on work using AWS tools like Kinesis and EMR.

Intermediate

Learn effective tips and techniques for passing the AWS Certified Machine Learning – Specialty exam
Identify and implement data ingestion solutions with Kinesis
Evaluate ML models
Deploy ML models with AWS tools

Job titles: ML engineer, DevOps engineer, Aspiring ML engineer

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