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Build Modern Applications with AWS NoSQL Databases

Written by Annika Thiemann on . Posted in AWS Training, Training.

  • Aws Advanced Training Partner

  • Aws Premium Consuting Partner

Build Modern Applications with AWS NoSQL Databases

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

Course description

This course is for developers, architects, and database engineers who want to build applications that involve complex data characteristics and millisecond performance requirements from their databases. In this course, you use AWS purpose-built databases to build a typical modern application with diverse access patterns and real-time scaling needs. By the end of the class, you should be able to describe advanced features of Amazon DynamoDB, Amazon DocumentDB (with Mongo compatibility), and Amazon ElastiCache for Redis.

Course objectives

In this course, you will learn to:

  • Build modern applications for the cloud using AWS purpose-built NoSQL databases

  • Illustrate solutions using AWS purpose-built databases for handling key-value, document, and in-memory data categories

  • Analyze business use cases and apply advanced features of Amazon DynamoDB to implement a scalable solution

  • Analyze business use cases and apply advanced features of Amazon ElastiCache to implement a scalable solution

  • Analyze business use cases and apply advanced features of Amazon DocumentDB to implement a scalable solution

  • Implement event-driven architectures using change streams and AWS Lambda

  • Learn how to build solutions faster with Amazon CodeWhisperer

Intended audience

This course is intended for experienced:

  • Database developers

  • Solutions Architects 

  • Database engineers

Prerequisites

We recommend that attendees of this course have:

  • Familiarity with cloud computing concepts

  • Familiarity with data modeling for relational or NoSQL databases

  • Working experience with Amazon DynamoDB table design

  • Working experience with Amazon DocumentDB table design

  • Working experience with ElastiCache for Redis

  • Familiarity with AWS Lambda and Amazon API Gateway database services

  • Familiarity with Python scripting

Activities

This course includes:

  • Presentations
  • Guided tours
  • Group discussions
  • Hands-on labs

Course duration / Price

  • 1 day
  • € 775,00 (excl. tax) per person

Course outline

Modul 1: Analyze Use Cases for NoSQL Databases

  • Business overview
  • Workload solution overview
  • AWS NoSQL database portfolio
  • Design decisions for a modern application

Modul 2: Advanced Amazon DynamoDB Concepts

  • Review business workloads for Amazon DynamoDB
  • Analyze access patterns and key design
  • Create the data model
  • Design for performance
  • Design event-driven architectures using DynamoDB Streams
  • Guided Tour: Design tables using NoSQL Workbench for DynamoDB
  • Guided Tour: Use DynamoDB Streams with AWS Lambda
  • Hands-on Lab: Implement Fleet and Trip Data Management using Amazon DynamoDB Tables, Indexes, and Change Streams

Modul 3: Advanced Amazon DocumentDB Concepts

  • Review business workloads for Amazon DocumentDB
  • Analyze access patterns
  • Create the data model
  • Design for performance
  • Use Amazon DocumentDB aggregation framework
  • Design event-driven architecture using Amazon DocumentDB
  • Guided Tour: Document and collection design
  • Guided Tour: Aggregation framework
  • Guided Tour: Use Amazon DocumentDB Change streams with AWS Lambda
  • Hands-on Lab: Implement and Optimize User Profile Data Management Workload on Amazon DocumentDB

Modul 4: Advanced Amazon ElastiCache for Redis Concepts

  • Review business workloads for Amazon ElastiCache for Redis
  • Analyze access patterns
  • Create the data model
  • Use optimal data structures for the workload
  • Guided Tour: Use Amazon ElastiCache for Redis to apply geospatial queries
  • Guided Tour: Use Amazon ElastiCache for Redis to natively store and access JSON data
  • Guided Tour: Use Amazon ElastiCache for Redis with leaderboards
  • Hands-on Lab: Implement Geospatial Bike Searches, User Profile Caching, and Leaderboards with Amazon ElastiCache for Redis

Modul 5: Course Summary

  • Course review
  • AWS Certification levels
  • Continue your learning

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.

Neue Termine in Planung!

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Generative AI for Executives

Written by Annika Thiemann on . Posted in AWS Training, Training.

  • Aws Advanced Training Partner

  • Aws Premium Consuting Partner

Generative AI for Executives

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

Course description

In this course, you will learn how to leverage generative artificial intelligence (AI) within your organization. We’ll cover how to drive business value with generative AI, the use cases across various industries, and the considerations to implement generative AI safely and responsibly. The goal of this course is to provide you with the fundamental concepts and tools you’ll need to successfully lead generative AI initiatives within your organization.

Course objectives

In this course, you will learn to:

  • Recognize the potential business value of generative AI

  • Identify real world use cases that you can implement today

  • Manage the people, process, and technology changes needed to be successful

  • Use generative AI safely and responsibly

  • Identify the specific steps you can take to get started with generative AI

Intended audience

This course is intended for experienced:

  • Executives and Senior Business Leaders

Prerequisites

  • None

Activities

This course includes:

  • Presentations
  • Group discussions

Course duration / Price

  • 0,5 days
  • € 395.00 (excl. tax) per person

Course outline

Modul 1: Introduction to Generative AI

  • Definitions and terminology
  • AWS approach to generative AI

Modul 2: Generative AI Use Cases

  • Common use cases
  • Real-world case studies

Modul 3: Overcoming Technical and Organizational Challenges

  • Security
  • Accuracy
  • Cost
  • People and culture

Modul 4: Implementation

  • Identifying your use case
  • Assessing data, technology, people, and processes
  • Evaluating business impact and scaling

Modul 5: Next Steps in Your Generative AI Journey

  • Next steps and additional resources
  • Course summary

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.

Neue Termine in Planung!

Continue reading

Designing and Implementing Storage on AWS

Written by Annika Thiemann on . Posted in AWS Training, Training.

  • Aws Advanced Training Partner

  • Aws Premium Consuting Partner

Designing and Implementing Storage on AWS

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

Course description

AWS offers a broad portfolio of storage services and solutions with diverse capabilities for storing, accessing, and protecting your data. In this course, you will learn where, how, and when to take advantage of these different service offerings. You will learn which services to consider when looking to solve your data storage challenges. You will learn how to best evaluate your options in selecting the appropriate AWS storage service to meet your use case and business requirements. You will also gain a better understanding of how to store, manage, and protect your data in the cloud. Through a series of hands-on exercises that demonstrate the ease and power of AWS platform, you will learn how to quickly provision powerful storage solutions in minutes.

Course objectives

In this course, you will learn to:

  • Describe the benefits of the core AWS storage services and identify some of their primary
    use cases

  • Select and design an appropriate storage solution according to application and business
    requirements

  • Configure storage resources to work with the broad array of AWS service offerings

  • Select the right method to move data between on-premises workloads and the AWS Cloud

  • Design storage solutions to protect data at rest and in transit

  • Set up monitoring and observability for Cloud storage to gain insight into access patterns,
    utilization, and efficiency

  • Design and optimize storage solutions according to cost, scalability, and performance
    requirements

Intended audience

This course is intended for:

  • Solutions Architects 

  • Cloud Storage Engineers 

  • Cloud Operations Specialists 

  • DevOps Engineers 

Prerequisites

We recommend that attendees of this course have:

Activities

This course includes:

  • Presentations
  • Hands-on labs
  • Demonstrations
  • Group exercises

Course duration / Price

  • 3 days
  • € 1,995.00 (excl. tax) per person

Course outline

  • Day 1

    • Modul 1: Introduction to Cloud Storage

      • Storage in the AWS cloud

      • Designing Well Architected Storage Solutions

      • Designing Durable and Available Storage Solutions

      • Building Accessible and Secure Storage Solutions

    • Modul 2: Designing Object Storage Solutions in AWS  

      • What is object storage?

      • Planning and designing your Amazon S3 deployment

      • Managing Amazon S3

      • Access Control with Amazon S3

      • Hands-On Lab: Exploring S3 Access Control and S3 Object Lambda

    • Modul 3: Implementing Object Storage solutions with S3

      • Cost management and the data lifecycle

      • Managing data transfers into Amazon S3

      • Data protection in Amazon S3

      • Manage objects stored in Amazon S3 at scale

      • Hands-on Lab: Multi-Part Uploads, Batch Operations, and Cross-Region Replication with
        Amazon S3

    • Modul 4: Designing Block storage solutions in AWS  
      • Block storage fundamentals
      • Amazon Elastic Block Store (Amazon EBS)
      • Configuring EBS volume types
      • EC2 and EBS encryption

  • Day 2

    • Module 5: Implementing Block Storage Solutions with Amazon EBS

      • Creating EBS volumes

      • Managing EBS volumes

      • Managing EBS snapshots at scale

      • Hands-On Lab: Managing EBS Volumes: Capacity, Performance, and Data Protection

    • Modul 6: File Storage and Amazon EFS

      • Cloud-based file storage

      • Amazon EFS overview

      • Accessing Amazon EFS

      • Securing and protecting Amazon EFS file systems

      • Hands-On Lab: Using Amazon EFS with AWS Lambda and Amazon ECS

    • Modul  7: Cloud file storage with Amazon FSx  

      • Amazon FSx overview

      • Amazon FSx for Windows File Server

      • Amazon FSx for NetAPP ONTAP

      • Amazon FSx for OpenZFS

      • Amazon FSx for Lustre

      • Choosing an Amazon FSx service

      • Hands-On Lab: Working with FSx for NetApp ONTAP and FSx for OpenZFS

  • Day 3

    • Modul 8: Hybrid and Edge Cloud Storage

      • Hybrid and edge cloud storage overview

      • Introduction to AWS Storage Gateway

      • AWS Storage Gateway architectures

      • AWS Snow Family

    • Modul 9: Moving data to AWS 

      • Moving data to AWS

      • Working with AWS DataSync

      • Implementing AWS Transfer Family

      • Hands-On Lab: Moving Data with Storage Gateway and DataSync

    • Modul 10: Backup and Disaster Recovery with AWS   

      • Designing a data protection strategy

      • AWS Backup

      • Creating backup plans

      • Working with AWS DRS

      • Hands-On Lab: Creating and Restoring Backups with AWS Backup

    • Modul 11: Monitoring, Automating, and Optimizing your AWS Storage  

      • AWS Observability Services

      • Amazon S3 Storage Lens

      • Amazon CloudWatch

      • AWS CloudTrail

      • AWS Config

      • AWS Compute Optimizer

      • Hands-On Lab: Storage Monitoring, Automation, and 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.

Neue Termine in Planung!

Continue reading

AWS Certified Data Engineer – Associate

Written by Gemma Corrado on . Posted in AWS Training, Certifications, Training.

Who should take this exam?

AWS Certified Data Engineer – Associate is designed for those who have experience in data engineering and understand the effects of volume, variety, and velocity on data ingestion, transformation, modeling, security, governance, privacy, schema design, and optimal data store design. You should also have hands-on experience with AWS services.

We recommend that you have the following knowledge before taking this exam:

  • Setup and maintenance of extract, transform, and load (ETL) pipelines from ingestion to destination
  • Application of high-level but language-agnostic programming concepts as required by the pipeline
  • How to use Git commands for source control
  • How to use data lakes to store data
  • General concepts for networking, storage, and compute
  • An understanding of the AWS services for encryption, governance, protection, and logging of all data that is part of data pipelines
  • The ability to compare AWS services to understand the cost, performance, and functional differences between services
  • How to structure SQL queries and how to run SQL queries on AWS services
  • An understanding of how to analyze data, verify data quality, and ensure data consistency by using AWS services

Prerequisites

The recommended experience prior to taking this exam is the equivalent of 2 to 3 years in data engineering or data architecture and at least 1 to 2 years of hands-on experience with AWS services.

Recertification

AWS Certifications are valid for three years. To maintain your AWS Certified status, we require you to periodically demonstrate your continued expertise though a process called recertification. Recertification helps strengthen the overall value of your AWS Certification and shows individuals and employers that your credential covers the latest AWS knowledge, skills, and best practices. Once you have obtained an AWS certification, you will receive a 50% discount on other AWS certification exams.

Developing Generative AI Applications on AWS

Written by Gemma Corrado on . Posted in AWS Training, Training.

  • Aws Advanced Training Partner

  • Aws Premium Consuting Partner

  • 200 Cert

Developing Generative AI Applications on AWS

Please find our upcoming course dates at the end of this page!

Course description

This course is designed to introduce generative artificial intelligence (AI) to software developers interested in using large language models (LLMs) without fine-tuning. The course provides an overview of generative AI, planning a generative AI project, getting started with Amazon Bedrock, the foundations of prompt engineering, and the architecture patterns to build generative AI applications using Amazon Bedrock and LangChain.

COURSE OBJECTIVES

In this course, you will learn to:

  • Describe generative AI and how it aligns to machine learning
  • Define the importance of generative AI and explain its potential risks and benefits
  • Identify business value from generative AI use cases
  • Discuss the technical foundations and key terminology for generative AI
  • Explain the steps for planning a generative AI project
  • Identify some of the risks and mitigations when using generative AI
  • Understand how Amazon Bedrock works
  • Familiarize yourself with basic concepts of Amazon Bedrock
  • Recognize the benefits of Amazon Bedrock
  • List typical use cases for Amazon Bedrock
  • Describe the typical architecture associated with an Amazon Bedrock solution
  • Understand the cost structure of Amazon Bedrock
  • Implement a demonstration of Amazon Bedrock in the AWS Management Console
  • Define prompt engineering and apply general best practices when interacting with foundation models (FMs)
  • Identify the basic types of prompt techniques, including zero-shot and few-shot learning
  • Apply advanced prompt techniques when necessary for your use case
  • Identify which prompt techniques are best suited for specific models
  • Identify potential prompt misuses
  • Analyze potential bias in FM responses and design prompts that mitigate that bias
  • Identify the components of a generative AI application and how to customize an FM
  • Describe Amazon Bedrock foundation models, inference parameters, and key Amazon Bedrock APIs
  • Identify Amazon Web Services (AWS) offerings that help with monitoring, securing, and governing your Amazon Bedrock applications
  • Describe how to integrate LangChain with LLMs, prompt templates, chains, chat models, text
    embeddings models, document loaders, retrievers, and Agents for Amazon Bedrock
  • Describe architecture patterns that you can implement with Amazon Bedrock for building generative AI applications
  • Apply the concepts to build and test sample use cases that use the various Amazon Bedrock models, LangChain, and the Retrieval Augmented Generation (RAG) approach

INTENDED AUDIENCE

This course is intended for:

  • Software developers interested in using LLMs without fine-tuning

PREREQUISITES

We recommend that attendees of this course have:

ACTIVITIES

This course includes:

  • Presentations
  • Demonstrations
  • Group exercises

COURSE DURATION / PRICE

  • 2 days
  • € 1,500.00 (excl. tax) per person (DE)

Course outline

  • Day 1

    • Module 1: Introduction to Generative AI – Art of the Possible
      • Overview of ML
      • Basics of generative AI
      • Generative AI use cases
      • Generative AI in practice
      • Risks and benefits
    • Module 2: Planning a Generative AI Project
      • Generative AI fundamentals
      • Generative AI in practice
      • Generative AI context
      • Steps in planning a generative AI project
      • Risks and mitigation
    • Module 3: Getting Started with Amazon Bedrock
      • Introduction to Amazon Bedrock
      • Architecture and use cases
      • How to use Amazon Bedrock
      • Demonstration: Setting up Bedrock access and using playgrounds
    • Module 4: Foundations of Prompt Engineering
      • Basics of foundation models
      • Fundamentals of prompt engineering
      • Basic prompt techniques
      • Advanced prompt techniques
      • Model-specific prompt techniques
      • Demonstration: Fine-tuning a basic text prompt
      • Addressing prompt misuses
      • Mitigating bias
      • Demonstration: Image bias mitigation

  • Day 2

    • Module 5: Amazon Bedrock Application Components
      • Overview of generative AI application components
      • Foundation models and the FM interface
      • Working with datasets and embeddings
      • Demonstration: Word embeddings
      • Additional application components
      • Retrieval Augmented Generation (RAG)
      • Model fine-tuning
      • Securing generative AI applications
      • Generative AI application architecture
    • Module 6: Amazon Bedrock Foundation Models
      • Introduction to Amazon Bedrock foundation models
      • Using Amazon Bedrock FMs for inference
      • Amazon Bedrock methods
      • Data protection and auditability
      • Demonstration: Invoke Bedrock model for text generation using zero-shot prompt
    • Module 7: LangChain
      • Optimizing LLM performance
      • Using models with LangChain
      • Constructing prompts
      • Demonstration: Bedrock with LangChain using a prompt that includes context
      • Structuring documents with indexes
      • Storing and retrieving data with memory
      • Using chains to sequence components
      • Managing external resources with LangChain agents
    • Module 8: Architecture Patterns
      • Introduction to architecture patterns
      • Text summarization
      • Demonstration: Text summarization of small files with Anthropic Claude
      • Demonstration: Abstractive text summarization with Amazon Titan using LangChain
      • Question answering
      • Demonstration: Using Amazon Bedrock for question answering
      • Chatbot
      • Demonstration: Conversational interface – Chatbot with AI21 LLM
      • Code generation
      • Demonstration: Using Amazon Bedrock models for code generation
      • LangChain and agents for Amazon Bedrock
      • Demonstration: Integrating Amazon Bedrock models with LangChain agents

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).
The Course language is German, on request also in English.

Neue Termine in Planung!

Continue reading