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Amazon Sagemaker Training

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Instructor-Led Training Parameters

Course Highlights

  • Instructor-led Online Training
  • Project Based Learning
  • Certified & Experienced Trainers
  • Course Completion Certificate
  • Lifetime e-Learning Access
  • 24x7 After Training Support

Amazon Sagemaker Training Course Overview

Amazon SageMaker Training offered by Multisoft Systems is a comprehensive program designed to equip learners with advanced skills in machine learning and artificial intelligence using Amazon SageMaker. This course is meticulously structured to provide participants with a deep understanding of building, training, and deploying machine learning models efficiently at scale. Through a blend of expert-led sessions, engaging hands-on labs, and real-world project work, learners will gain practical experience in managing the entire machine learning workflow.

The curriculum covers crucial topics such as data preparation, model building, tuning, deployment, and security practices within the SageMaker environment. Participants will learn how to leverage SageMaker's fully managed instances and auto-scaling capabilities to streamline their machine learning projects. By the end of the course, attendees will have mastered the tools and techniques necessary to implement AI solutions, making them valuable assets in technology-driven industries. This training is ideal for professionals seeking to advance their careers in AI and machine learning.

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Amazon Sagemaker Training Course curriculum

Curriculum Designed by Experts

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Amazon SageMaker Training offered by Multisoft Systems is a comprehensive program designed to equip learners with advanced skills in machine learning and artificial intelligence using Amazon SageMaker. This course is meticulously structured to provide participants with a deep understanding of building, training, and deploying machine learning models efficiently at scale. Through a blend of expert-led sessions, engaging hands-on labs, and real-world project work, learners will gain practical experience in managing the entire machine learning workflow.

The curriculum covers crucial topics such as data preparation, model building, tuning, deployment, and security practices within the SageMaker environment. Participants will learn how to leverage SageMaker's fully managed instances and auto-scaling capabilities to streamline their machine learning projects. By the end of the course, attendees will have mastered the tools and techniques necessary to implement AI solutions, making them valuable assets in technology-driven industries. This training is ideal for professionals seeking to advance their careers in AI and machine learning.

  • Learn the fundamentals and advanced features of Amazon SageMaker, including how to build, train, and deploy machine learning models efficiently.
  • Acquire practical skills through hands-on labs and projects that simulate real-world AI challenges, enabling you to apply what you've learned immediately.
  • Understand how to seamlessly deploy your machine learning models and manage them in a production environment using Amazon SageMaker's capabilities.
  • Absorb best practices for machine learning workflows, including data preparation, model tuning, and optimization, to ensure your projects are both efficient and scalable.
  • Develop skills that are in high demand in the tech industry, making you a competitive candidate for roles requiring expertise in machine learning and AI.

Course Prerequisite

  • Basic understanding of machine learning concepts and algorithms
  • Familiarity with Python programming language
  • Knowledge of data science and analytics fundamentals
  • Basic experience with AWS (Amazon Web Services) or cloud computing concepts
  • Course Certification
  • Multisoft Systems provides a globally recognized training certificate after successful completion of Amazon Sagemaker training certification course.

Course Target Audience

  • Data Scientists
  • Machine Learning Engineers
  • Developers interested in ML and AI
  • IT Professionals looking to specialize in AI/ML
  • Product Managers wanting to leverage AI/ML in products
  • Cloud Computing Specialists focusing on AWS services

Course Content

  • Types of ML
  • Job Roles in ML
  • Steps in the ML pipeline

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  • Training and test dataset defined
  • Introduction to SageMaker
  • Demonstrate the SageMaker console
  • Demonstrate the Launching a Jupyter notebook

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  • Business challenge: Customer churn
  • Review customer churn dataset

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  • Demonstration: Loading and visualizing your dataset
  • Relate features to target variables
  • Relationships between attributes
  • Demonstrate how to clean the data

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  • Types of algorithms
  • XGBoost and SageMaker
  • Demonstrate how to train the data
  • Finish the estimator definition
  • Set hyper parameters
  • Deploy the model
  • Demonstrate the hyper parameter tuning with SageMaker
  • Demonstrate the evaluating model performance

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  • Automatic hyper parameter tuning with SageMaker
  • Exercises 6-9: Tune jobs

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  • Deploy a model to an endpoint
  • A/B deployment for testing
  • Auto Scaling
  • Demonstrate how to configure and test auto scaling
  • Demonstrate how to check hyper parameter tuning job
  • Demonstrate the AWS Auto Scaling
  • Set up AWS Auto Scaling

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  • Cost of various error types
  • Binary classification cutoff

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  • Access Amazon SageMaker notebooks in a VPC
  • Amazon SageMaker batch transforms
  • Amazon SageMaker Ground Truth
  • Amazon SageMaker Neo

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Amazon Sagemaker Training (MCQ) Assessment

This assessment tests understanding of course content through MCQ and short answers, analytical thinking, problem-solving abilities, and effective communication of ideas. Some Multisoft Assessment Features :

  • User-friendly interface for easy navigation
  • Secure login and authentication measures to protect data
  • Automated scoring and grading to save time
  • Time limits and countdown timers to manage duration.
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Amazon Sagemaker Corporate Training

Employee training and development programs are essential to the success of businesses worldwide. With our best-in-class corporate trainings you can enhance employee productivity and increase efficiency of your organization. Created by global subject matter experts, we offer highest quality content that are tailored to match your company’s learning goals and budget.

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Customized Training

Be it schedule, duration or course material, you can entirely customize the trainings depending on the learning requirements

Expert
Mentors

Be it schedule, duration or course material, you can entirely customize the trainings depending on the learning requirements

360º Learning Solution

Be it schedule, duration or course material, you can entirely customize the trainings depending on the learning requirements

Learning Assessment

Be it schedule, duration or course material, you can entirely customize the trainings depending on the learning requirements

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Certification Training Achievements: Recognizing Professional Expertise

Multisoft Systems is the “one-top learning platform” for everyone. Get trained with certified industry experts and receive a globally-recognized training certificate. Some Multisoft Training Certificate Features :

  • Globally recognized certificate
  • Course ID & Course Name
  • Certificate with Date of Issuance
  • Name and Digital Signature of the Awardee
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Amazon Sagemaker Training FAQ's

  • This training is ideal for data scientists, machine learning engineers, developers interested in AI/ML, and IT professionals looking to specialize in AI/ML technologies.

  • You will learn how to use Amazon SageMaker to build, train, and deploy machine learning models efficiently. The course covers everything from basic to advanced SageMaker features, including data preparation, model tuning, and deployment.

  • Basic experience with AWS or cloud computing concepts is recommended. Familiarity with the AWS platform will help you grasp the course content more effectively.

  • Yes, participants should have a basic understanding of machine learning concepts, familiarity with the Python programming language, and knowledge of data science fundamentals.

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