Amazon SageMaker Training - United States

Amazon SageMaker Training Course Outline

Module 1: Introduction to Amazon SageMaker

• What is Amazon SageMaker?
• Machine Learning with Amazon SageMaker
• Explore and Preprocess Data
• Model Training and Deployment

Module 2: Setting Up Amazon SageMaker

• Create an IAM Administrator User and Group

Module 3: Get Started with Amazon SageMaker

• Create an Amazon S3 Bucket
• Create an Amazon SageMaker Notebook Instance
• Create a Jupyter Notebook
• Download, Explore, and Transform Data
• Train, Deploy, and Validate Model
• Clean Up

Module 4: Using Notebook Instances

• Create and Access Notebook Instances
• Use Example Notebooks
• Notebook Instance Software Updates
• Setting the Notebook Kernel
• Installing External Libraries and Kernels in Notebook Instances
• Creating Git Repositories with Amazon SageMaker Notebook Instances
• Monitoring Jupyter Logs in Amazon CloudWatch Logs

Module 5: Build, Train, and Deploy a Model

• Built-in Algorithms
• Incremental Training
• Managed Spot Training
• Using Checkpoints
• Automatic Model Tuning
• Augmented Manifest Files
• Amazon SageMaker Neo

Module 6: Amazon SageMaker with ECR

• Basics of Docker Containers
• Amazon SageMaker Containers
• Use Prebuilt SageMaker Docker Images
• Creating Training Job with ECR

Module 7: Reinforcement Learning with Amazon SageMaker RL

• Markov Decision Process (MDP)
• Sample RL Workflow Using Amazon SageMaker RL
• RL Environments in Amazon SageMaker
• Distributed Training
• Hyperparameter Tuning

Module 8: Security in Amazon SageMaker

• Data Protection
• Identity and Access Management
• Logging and Monitoring
• Compliance Validation

Who should attend this Amazon SageMaker Training Course?

The Amazon SageMaker Training Course is designed for individuals who want to gain an understanding of machine learning and deploy the same for practical applications. The Amazon SageMaker Training Course can benefit professionals such as:

• Data Scientists
• Machine Learning Engineers
• Data Engineers
• Data Analysts
• Cloud Architects
• Financial Analysts
• Technical Managers

Prerequisites of the Amazon SageMaker Training Course

There are no formal prerequisites for this Amazon SageMaker Course. However, a basic understanding of machine learning can be beneficial for the delgates.

Amazon SageMaker Training Course Overview

Amazon SageMaker,a pivotal service within the AWS (Amazon Web Service) cloud, revolutionizes machine learning model development, training, and deployment. This training provides an in-depth exploration of Amazon SageMaker, empowering participants with the skills to harness the potential of machine learning in AWS. Understanding SageMaker is crucial as it enables developers to build and train machine learning models for predictive or analytical applications.

Professionals specializing in machine learning, data science, and cloud computing are well-positioned to benefit significantly from mastering Amazon SageMaker. This course is particularly relevant for developers, data engineers, and AI practitioners who aim to enhance their proficiency in building and deploying machine learning models using SageMaker.

This 2-days training by The Knowledge Academy offers a comprehensive learning experience, covering essential aspects such as running training jobs, hyperparameter tuning, model packaging, and reinforcement learning with Amazon SageMaker RL. Delegates will gain hands-on experience with popular machine learning frameworks like Apache Spark, TensorFlow, and Apache MXNet.

Course Objectives

• To run a training job, hyperparameter tuning job, and create a model using Amazon SageMaker
• To become familiar with machine learning frameworks, including Apache Spark, TensorFlow, and Apache MXNet
• To gain in-depth knowledge of reinforcement learning with Amazon SageMaker RL
• To understand the use of Jupyter notebooks and their role in collaborative and interactive machine learning development
• To learn how to protect data at rest and in transit using encryption in Amazon SageMaker
• To acquire practical skills for deploying machine learning models using Amazon SageMaker

Upon completing this course, delegates will benefit by gaining expertise in Amazon SageMaker, positioning themselves as proficient contributors to machine learning projects in AWS. The practical knowledge acquired during the training empowers participants to leverage SageMaker effectively, enhancing their capabilities in building, training, and deploying machine learning models for real-world applications in the cloud.

What’s included in this Amazon SageMaker Training Course?

• World-Class Training Sessions from Experienced Instructors
• Amazon SageMaker Certificate
• Digital Delegate Pack

You’ll also get access to the MyTKA Training Portal, which will be your go to hub for all your training.
Hands-On Labs: Included as part of our online instructor-led delivery, these labs provide real-world exercises in a simulated environment guided by expert instructors to enhance your practical skills.