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AWS Cloud Essentials for Business Leaders

Written by wamrhein on . Posted in AWS Training, Training.

AWS Cloud Essentials for Business Leaders

current course dates can be found at the bottom of this page … company training available on request!

Course description

This course is for business leaders who seek an overall understanding of the fundamental concepts of cloud computing. Learn how a cloud strategy can help you meet business objectives. The course dives into the business value of the cloud through customer examples, exploring industry trends, and the Cloud Value Framework, which helps you understand the business value of building on AWS by assessing cost and value impact.

Course objectives

In this course, you will learn to:

  • Explain the role of information technology (IT) in an organization for business transformation
  • Explain the customer value proposition for using the cloud across industries
  • Define key characteristics of cloud computing
  • Explain the cloud business model
  • Identify key security practices of cloud computing
  • Frame the cloud business value using the Cloud Value Framework

Intended audience

This course is intended for:

  • Line of Business (LoB) owners and executives

Prerequisites

We recommend that attendees of this course have:

  • No prior IT experience or cloud experience is required.

Activities

This course includes:

  • Training with instructor
    Practical exercises

Course duration / Price

  • 4 hours / € 750.00 (excl. tax) per person (DE)

Course outline

Module 1: Course Introduction

Module 2: Information Technology for Business Transformation

  • Role of IT in an organization for business transformation
  • Brief history of IT
  • Legacy approach to IT
  • What drives customers to move from traditional infrastructure to the cloud

Module 3: Cloud Computing

  • Define cloud computing
  • Key characteristics of cloud technology
  • The cloud business model
  • Key security practices within the cloud

Module 4: Business Value of the Cloud

  • The customer value proposition
  • Identify who is using cloud computing
  • Industry trends
  • Customer examples

Module 5: The Cloud Value Framework

  • Introduction to the Cloud Value Framework
  • Cost Savings
  • Staff Productivity
  • Operational Resilience
  • Business Agility

Module 6: Business Value Activity

  • Using a fictional customer case study, we review and apply lessons learned from the course

IMPORTANT: Please bring your notebook (Windows, Linux or Mac) to our trainings. If this is not possible, please contact us in advance.

Course materials are in English, on request also in German (if available).
Course language is German, on request also in English.

AWS Cloud Essentials for Business Leaders – Financial Services

Written by wamrhein on . Posted in AWS Training, Training.

AWS Cloud Essentials for Business Leaders – Financial Services

current course dates can be found at the bottom of this page … company training available on request!

Course description

This course is for business leaders who seek an overall understanding of the fundamental concepts of cloud computing. Learn how a cloud strategy can help you meet business objectives. In this half-day, instructor-led course, you’ll explore the possibilities of cloud computing in banking, insurance, capital markets, payments, and financial technology. The course dives into the business value of the cloud through customer examples, exploring industry trends, and the Cloud Value Framework, which helps you understand the business value of building on AWS by assessing cost and value impact.

 

Course objectives

In this course, you will learn to:

  • Explain the role of information technology (IT) in an organization for business transformation
  • Explain the customer value proposition for using the cloud in the financial services industry (FSI)
  • Define key characteristics of cloud computing
  • Explain the cloud business model
  • Identify key Financial Services Industry (FSI) security practices of cloud computing
  • Frame the cloud business value using the Cloud Value Framework

Intended audience

This course is intended for:

  • Line of business (LOB) owners and executives

Prerequisites

We recommend that attendees of this course have:

  • No prior IT experience or cloud experience is required

Activities

This course includes:

  • Training with instructor
  • Practical exercises

Kursdauer / Preis

  • 4 hours / € 750.00 (excl. tax) per person (DE)

Course outline

Module 1: Course Introduction

Module 2: Information Technology for Business Transformation

  • Role of IT in an organization for business transformation
  • Brief history of IT
  • Legacy approach to IT
  • What drives customers to move from traditional infrastructure to the cloud

Module 3: Cloud Computing

  • Define cloud computing
  • Key characteristics of cloud technology
  • The cloud business model
  • Key FIS security practices within the cloud

Module 4: Business Value of the Cloud

  • The customer value proposition
  • Identify who is using cloud computing
  • Industry trends
  • Customer examples

Module 5: The Cloud Value Framework

  • Introduction to the Cloud Value Framework
  • Cost Savings
  • Staff Productivity
  • Operational Resilience
  • Business Agility

Module 6: Business Value Activity

  • Using a fictional customer case study, we review and apply lessons learned from the course

IMPORTANT: Please bring your notebook (Windows, Linux or Mac) to our trainings. If this is not possible, please contact us in advance.

Course materials are in English, on request also in German (if available).
Course language is German, on request also in English.

AWS Well-Architected Best Practices

Written by wamrhein on . Posted in AWS Training, Training.

AWS Well-Architected Best Practices

current course dates can be found at the bottom of this page … company training available on request!

Course description

The AWS Well-Architected Best Practices course will help you learn a consistent approach to evaluate architectures and implement designs from a live instructor. You’ll learn how to use the Well-Architected Review process and the AWS Well-Architected Tool to conduct reviews to identify high risk issues (HRIs). In this 1-day, classroom training course, you’ll learn to apply the five pillars of the AWS Well-Architected Framework—operational excellence, security, reliability, performance efficiency, and cost optimization—to understand the impact of design decisions. You’ll apply what you’ve learned during the course to each pillar of the Well-Architected Framework through tutorials, hands-on labs, discussions, demonstrations, presentations, and group exercises.

Course objectives

In this course, you will learn to:

  • Identify the Well-Architected Framework features, design principles, design pillars, and common uses
  • Apply the design principles, key services, and best practices for each pillar of the Well-Architected Framework
  • Use the Well-Architected Tool to conduct Well-Architected Reviews

Intended audience

This course is intended for:

  • Technical professionals involved in architecting, building, and operating AWS solutions.

Prerequisites

We recommend that attendees of this course have:

Activities

This course includes:

  • Training with instructor
  • Practical exercises

Course duration / Price

  • 1 day / € 750.00 (excl. tax) per person (DE)

Course outline

Module 1: Well-Architected Introduction

  • History of Well-Architected
  • Goals of Well-Architected
  • What is the AWS Well-Architected Framework?
  • The AWS Well-Architected Tool

Module 2: Design Principles

  • Operational Excellence
  • Lab 1: Operational Excellence
  • Reliability
  • Lab 2: Reliability
  • Security
  • Lab 3: Security
  • Performance Efficiency
  • Lab 4: Performance Efficiency
  • Cost Optimization
  • Lab 5: Cost Optimization

 

IMPORTANT: Please bring your notebook (Windows, Linux or Mac) to our trainings. If this is not possible, please contact us in advance.

Course materials are in English, on request also in German (if available).
Course language is German, on request also in English.

AWS Security Governance at Scale

Written by wamrhein on . Posted in AWS Training, Training.

AWS Security Governance at Scale

current course dates can be found at the bottom of this page … company training available on request!

Course description

Security is foundational to AWS. Governance at scale is a new concept for automating cloud governance that can help companies retire manual processes in account management, budget enforcement, and security and compliance. By automating common challenges, companies can scale without inhibiting agility, speed, or innovation. In addition, they can provide decision makers with the visibility, control, and governance necessary to protect sensitive data and systems.

In this course, you will learn how to facilitate developer speed and agility, and incorporate preventive and detective controls. By the end of this course, you will be able to apply governance best practices.

Course objectives

In this course, you will learn to:

  • Establish a landing zone with AWS Control Tower
  • Configure AWS Organizations to create a multi-account environment
  • Implement identity management using AWS Single Sign-On users and groups
  • Federate access using AWS SSO
  • Enforce policies using prepackaged guardrails
  • Centralize logging using AWS CloudTrail and AWS Config
  • Enable cross-account security audits using AWS Identity and Access Management (IAM)
  • Define workflows for provisioning accounts using AWS Service Catalog and AWS Security Hub

Intended audience

This course is intended for:

  • Solutions architects
  • Security DevOps
  • Security engineers

Prerequisites

We recommend that attendees of this course have:

Activities

This course includes:

  • Training with instructor
  • Practical exercises

Course duration / Price

  • 1 day / € 895.00 (excl. tax) per person (DE)

Course outline

Course Introduction

  • Instructor introduction
  • Learning objectives
  • Course structure and objectives
  • Course logistics and agenda

Module 1: Governance at Scale

  • Governance at scale focal points
  • Business and Technical Challenges

Module 2: Governance Automation

  • Multi-account strategies, guidance, and architecture
  • Environments for agility and governance at scale
  • Governance with AWS Control Tower
  • Use cases for governance at scale

Module 3: Preventive Controls

  • Enterprise environment challenges for developers
  • AWS Service Catalog
  • Resource creation
  • Workflows for provisioning accounts
  • Preventive cost and security governance
  • Self-service with existing IT service management (ITSM) tools
  • Lab 1: Deploy Resources for AWS Catalog
  • Create a new AWS Service Catalog portfolio and product
  • Add an IAM role to a launch constraint to limit the actions the product can perform
  • Grant access for an IAM role to view the catalog items
  • Deploy an S3 bucket from an AWS Service Catalog product

Module 4: Detective Controls

  • Operations aspect of governance at scale
  • Resource monitoring
  • Configuration rules for auditing
  • Operational insights
  • Remediation Clean up accounts
  • Lab 2: Compliance and Security Automation with AWS Config
  • Apply Managed Rules through AWS Config to selected resources
  • Automate remediation based on AWS Config rules
  • Investigate the Amazon Config dashboard and verify resources and rule compliance
  • Lab 3: Taking Action with AWS Systems Manager
  • Setup Resource Groups for various resources based on common requirements
  • Perform automated actions against targeted Resource Groups

Module 5: Resources

  • Explore additional resources for security governance at scale

 

IMPORTANT: Please bring your notebook (Windows, Linux or Mac) to our trainings. If this is not possible, please contact us in advance.

Course materials are in English, on request also in German (if available).
Course language is German, on request also in English.

MLOps Engineering on AWS

Written by wamrhein on . Posted in AWS Training, Training.

MLOps Engineering on AWS

current course dates can be found at the bottom of this page … company training available on request!

Course description

This course builds upon and extends the DevOps practice prevalent in software development to build, train, and deploy machine learning (ML) models. The course stresses the importance of data, model, and code to successful ML deployments. It will demonstrate the use of tools, automation, processes, and teamwork in addressing the challenges associated with handoffs between data engineers, data scientists, software developers, and operations. The course will also discuss the use of tools and processes to monitor and take action when the model prediction in production starts to drift from agreed-upon key performance
indicators.

The instructor will encourage the participants in this course to build an MLOps action plan for their organization through daily reflection of lesson and lab content, and through conversations with peers and instructors.

Course objectives

In this course, you will learn to:

  • Describe machine learning operations
  • Understand the key differences between DevOps and MLOps
  • Describe the machine learning workflow
  • Discuss the importance of communications in MLOps
  • Explain end-to-end options for automation of ML workflows
  • List key Amazon SageMaker features for MLOps automation
  • Build an automated ML process that builds, trains, tests, and deploys models
  • Build an automated ML process that retrains the model based on change(s) to the model code
  • Identify elements and important steps in the deployment process
  • Describe items that might be included in a model package, and their use in training or inference
  • Recognize Amazon SageMaker options for selecting models for deployment, including support for ML frameworks and built-in algorithms or bring-your-own-models
  • Differentiate scaling in machine learning from scaling in other applications
  • Determine when to use different approaches to inference
  • Discuss deployment strategies, benefits, challenges, and typical use cases
  • Describe the challenges when deploying machine learning to edge devices
  • Recognize important Amazon SageMaker features that are relevant to deployment and inference
  • Describe why monitoring is important
  • Detect data drifts in the underlying input data
  • Demonstrate how to monitor ML models for bias
  • Explain how to monitor model resource consumption and latency
  • Discuss how to integrate human-in-the-loop reviews of model results in production

Intended audience

This course is intended for:

  • DevOps Engineers
  • ML Engineers
  • Developers/operations with responsibility for operationalizing ML models

Prerequisites

We recommend that attendees of this course have:

Activities

This course includes:

  • Training with instructor
  • Practical exercises

Course duration / Price

  • 3 days / € 2,685.00 (excl. tax) per person (DE)

Course outline

Module 1: Security on AWS

  • Machine learning operations
  • Goals of MLOps
  • Communication
  • From DevOps to MLOps
  • ML workflow
  • Scope
  • MLOps view of ML workflow
  • MLOps cases

Module 2: MLOps Development

  • Intro to build, train, and evaluate machine learning models
  • MLOps security
  • Automating
  • Apache Airflow
  • Kubernetes integration for MLOps
  • Amazon SageMaker for MLOps
  • Lab: Bring your own algorithm to an MLOps pipeline
  • Demonstration: Amazon SageMaker
  • Lab: Code and serve your ML model with AWS CodeBuild
  • Activity: MLOps Action Plan Workbook

Module 3: MLOps Deployment

  • Introduction to deployment operations
  • Model packaging
  • Inference
  • Lab: Deploy your model to production
  • SageMaker production variants
  • Deployment strategies
  • Deploying to the edge
  • Lab: Conduct A/B testing
  • Activity: MLOps Action Plan Workbook

Module 4: Model Monitoring and Operations

  • Lab: Troubleshoot your pipeline
  • The importance of monitoring
  • Monitoring by design
  • Lab: Monitor your ML model
  • Human-in-the-loop
  • Amazon SageMaker Model Monitor
  • Demonstration: Amazon SageMaker Pipelines, Model Monitor, model registry, and Feature Store
  • Solving the Problem(s)
  • Activity: MLOps Action Plan Workbook

Module 5: Wrap-up

  • Course review
  • Activity: MLOps Action Plan Workbook
  • Wrap-up

IMPORTANT: Please bring your notebook (Windows, Linux or Mac) to our trainings. If this is not possible, please contact us in advance.

Course materials are in English, on request also in German (if available).
Course language is German, on request also in English.