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Machine Learning Engineering on AWS

Learn how to transform your ML expertise into real-world solutions from an expert AWS Instructor

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Machine Learning Engineering on AWS

Transform your ML expertise into production-scale solutions on AWS. Learn to build, deploy, and operationalize machine learning applications using HAQM SageMaker and EMR. Perfect for ML professionals seeking AWS certification, this hands-on course delivers practical skills for implementing enterprise-grade ML solutions in this three-day course.

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Course details

  • Level: Intermediate
  • Type: Classroom (virtual and in person)
  • Length: 3 days
  • Explain the fundamentals of machine learning and its applications on the AWS platform.
  • Process, transform, and engineer data for machine learning tasks using AWS services, like HAQM SageMaker Data Wrangler, HAQM EMR, and SageMaker Processing.
  • Select appropriate machine learning algorithms and modeling approaches based on problem requirements and model interpretability.
  • Design and implement scalable machine learning pipelines using AWS services for model training, deployment, and orchestration.
  • Create automated CI/CD pipelines for machine learning workflows.
  • Discuss appropriate security measures for machine learning resources on AWS.
  • Implement monitoring strategies for deployed machine learning models, including techniques for detecting data drift.
  • Machine Learning Engineers
  • DevOps Engineers
  • Developers
  • SysOps Engineers
  • Familiarity with basic machine learning concepts, such as supervised and unsupervised learning, regression, classification, and clustering algorithms.
  • Working knowledge of Python programming language and common data science libraries like NumPy, Pandas, and Scikit-learn.
  • Basic understanding of cloud computing concepts and familiarity with the AWS platform.
  • Familiarity with SQL and relational databases is recommended but not mandatory.
  • Experience with version control systems like Git is beneficial but not required.

This course is offered in the following languages: English.

We regularly update our courses based on customer feedback and AWS service updates. As a result, course content may vary between languages while we localize these updates.