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Embark on Your Machine Learning Journey with AWS.

Introduction to Machine Learning on AWS

1600,-€ (excl. VAT)

Cost

5 Days

Duration

Participants will gain a solid understanding of machine learning fundamentals and how AWS services can be leveraged to build and deploy ML models. You'll learn about data preparation, model training, evaluation, and deployment, preparing you to start implementing basic machine learning solutions.

Learning Objectives

A basic understanding of AWS services is helpful but not mandatory. Familiarity with general machine learning concepts and some programming or data science experience would be beneficial.

Prerequisites

This course is designed for beginners in machine learning and AWS users interested in understanding how to apply machine learning on the cloud. It's perfect for IT professionals, data analysts, developers, or any curious minds looking to understand machine learning's practical aspects on AWS.

Who Should Attend

Begin your journey into the realm of Machine Learning on AWS with this comprehensive introductory course. Over an immersive learning experience, understand how AWS provides the tools and services to build, train, and deploy machine learning models efficiently. This course covers foundational machine learning concepts, AWS's pivotal machine learning services, and practical examples to demonstrate how you can implement ML solutions effectively. Whether you're looking to apply machine learning in your business or kickstart a career in this exciting field, this course will provide the knowledge and skills you need.

Course Description

  • Module 1: Introduction to Machine Learning: Understanding ML, its applications, and potential.

  • Module 2: AWS Machine Learning Services Overview: Exploring AWS services like SageMaker, Lex, and Polly.

  • Module 3: Data Engineering on AWS: Best practices for data preparation and processing.

  • Module 4: Building Machine Learning Models: An introduction to model development and training.

  • Module 5: Model Evaluation and Optimization: Techniques for assessing and enhancing model performance.

  • Module 6: Deployment and Operationalization: Deploying models and integrating them with applications.

  • Module 7: Real-World Applications and Case Studies: Exploring practical examples and success stories.

  • Module 8: The Future of ML on AWS: Insights into emerging trends and opportunities.

Course Outline

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Karl-Gruneklee Strasse 22,

37077, Gottingen

Germany

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