277 Amazon courses in Sheffield delivered Live Online

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Solutions architects, cloud engineers, including security engineers, delivery and implementation engineers, professional services, and Cloud Center of Excellence (CCOE) Overview In this course, you will learn to: Design and implement a secure network infrastructure Design and implement compute security Design and implement a logging solution Currently, the average cost of a security breach can be upwards of $4 million. AWS Security Best Practices provides an overview of some of the industry best practices for using AWS security and control types. This course helps you understand your responsibilities while providing valuable guidelines for how to keep your workload safe and secure. You will learn how to secure your network infrastructure using sound design options. You will also learn how you can harden your compute resources and manage them securely. Finally, by understanding AWS monitoring and alerting, you can detect and alert on suspicious events to help you quickly begin the response process in the event of a potential compromise. Module 1: AWS Security Overview Shared responsibility model Customer challenges Frameworks and standards Establishing best practices Compliance in AWS Module 2: Securing the Network Flexible and secure Security inside the Amazon Virtual Private Cloud (Amazon VPC) Security services Third-party security solutions Module 3: Amazon EC2 Security Compute hardening Amazon Elastic Block Store (EBS) encryption Secure management and maintenance Detecting vulnerabilities Using AWS Marketplace Module 4: Monitoring and Alerting Logging network traffic Logging user and Application Programming Interface (API) traffic Visibility with Amazon CloudWatch Enhancing monitoring and alerting Verifying your AWS environment Additional course details: Nexus Humans AWS Security Best Practices training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the AWS Security Best Practices course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Data platform engineers Solutions architects IT professionals Overview In this course, you will learn to: Apply data lake methodologies in planning and designing a data lake Articulate the components and services required for building an AWS data lake Secure a data lake with appropriate permission Ingest, store, and transform data in a data lake Query, analyze, and visualize data within a data lake In this course, you will learn how to build an operational data lake that supports analysis of both structured and unstructured data. You will learn the components and functionality of the services involved in creating a data lake. You will use AWS Lake Formation to build a data lake, AWS Glue to build a data catalog, and Amazon Athena to analyze data. The course lectures and labs further your learning with the exploration of several common data lake Introduction to data lakes Describe the value of data lakes Compare data lakes and data warehouses Describe the components of a data lake Recognize common architectures built on data lakes Data ingestion, cataloging, and preparation Describe the relationship between data lake storage and data ingestion Describe AWS Glue crawlers and how they are used to create a data catalog Identify data formatting, partitioning, and compression for efficient storage and query Lab 1: Set up a simple data lake Data processing and analytics Recognize how data processing applies to a data lake Use AWS Glue to process data within a data lake Describe how to use Amazon Athena to analyze data in a data lake Building a data lake with AWS Lake Formation Describe the features and benefits of AWS Lake Formation Use AWS Lake Formation to create a data lake Understand the AWS Lake Formation security model Lab 2: Build a data lake using AWS Lake Formation Additional Lake Formation configurations Automate AWS Lake Formation using blueprints and workflows Apply security and access controls to AWS Lake Formation Match records with AWS Lake Formation FindMatches Visualize data with Amazon QuickSight Lab 3: Automate data lake creation using AWS Lake Formation blueprints Lab 4: Data visualization using Amazon QuickSight Architecture and course review Post course knowledge check Architecture review Course review

Duration 3 Days 18 CPD hours This course is intended for Experienced software developers who are already familiar with AWS services Overview In this course, you will learn how to: Analyze a monolithic application architecture to determine logical or programmatic break points where the application can be broken up across different AWS services Apply Twelve-Factor Application manifesto concepts and steps while migrating from a monolithic architecture Recommend the appropriate AWS services to develop a microservices based cloud-native application Use the AWS API, CLI, and SDKs to monitor and manage AWS services Migrate a monolithic application to a microservices application using the 6 Rs of migration Explain the SysOps and DevOps interdependencies necessary to deploy a microservices application in AWS The Advanced Developing on AWS course uses the real-world scenario of taking a legacy, on-premises monolithic application and refactoring it into a serverless microservices architecture. This three-day advanced course covers advanced development topics such as architecting for a cloud-native environment; deconstructing on-premises, legacy applications and repackaging them into cloud-based, cloud-native architectures; and applying the tenets of the Twelve-Factor Application methodology. Module 1: The cloud journey Common off-cloud architecture Introduction to Cloud Air Monolithic architecture Migration to the cloud Guardrails The six R?s of migration The Twelve-Factor Application Methodology Architectural styles and patterns Overview of AWS Services Interfacing with AWS Services Authentication Infrastructure as code and Elastic Beanstalk Demonstration: Walk through creating base infrastructure with AWS CloudFormation in the AWS console Hands-on lab 1: Deploy your monolith application using AWS Elastic Beanstalk Module 2: Gaining Agility DevOps CI/CD Application configuration Secrets management CI/CD Services in AWS Demonstration: Demo AWS Secrets Manager Module 3: Monolith to MicroServices Microservices Serverless A look at Cloud Air Microservices using Lambda and API Gateway SAM Strangling the Monolith Hands-on lab: Using AWS Lambda to develop microservices Module 4: Polyglot Persistence & Distributed Complexity Polyglot persistence DynamoDB best practices Distributed complexity Steps functions Module 5: Resilience and Scale Decentralized data stores Amazon SQS Amazon SNS Amazon Kinesis Streams AWS IoT Message Broker Serverless event bus Event sourcing and CQRS Designing for resilience in the cloud Hands-on lab: Exploring the AWS messaging options Module 6: Security and Observability Serverless Compute with AWS Lambda Authentication with Amazon Cognito Debugging and traceability Hands-on lab: Developing microservices on AWS Additional course details: Nexus Humans Advanced Developing on AWS training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Advanced Developing on AWS course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Data platform engineers Solutions architects IT professionals Overview In this course, you will learn to: Apply data lake methodologies in planning and designing a data lake Articulate the components and services required for building an AWS data lake Secure a data lake with appropriate permission Ingest, store, and transform data in a data lake Query, analyze, and visualize data within a data lake In this course, you will learn how to build an operational data lake that supports analysis of both structured and unstructured data. You will learn the components and functionality of the services involved in creating a data lake. You will use AWS Lake Formation to build a data lake, AWS Glue to build a data catalog, and Amazon Athena to analyze data. The course lectures and labs further your learning with the exploration of several common data lake architectures. Module 1: Introduction to data lakes Describe the value of data lakes Compare data lakes and data warehouses Describe the components of a data lake Recognize common architectures built on data lakes Module 2: Data ingestion, cataloging, and preparation Describe the relationship between data lake storage and data ingestion Describe AWS Glue crawlers and how they are used to create a data catalog Identify data formatting, partitioning, and compression for efficient storage and query Lab 1: Set up a simple data lake Module 3: Data processing and analytics Recognize how data processing applies to a data lake Use AWS Glue to process data within a data lake Describe how to use Amazon Athena to analyze data in a data lake Module 4: Building a data lake with AWS Lake Formation Describe the features and benefits of AWS Lake Formation Use AWS Lake Formation to create a data lake Understand the AWS Lake Formation security model Lab 2: Build a data lake using AWS Lake Formation Module 5: Additional Lake Formation configurations Automate AWS Lake Formation using blueprints and workflows Apply security and access controls to AWS Lake Formation Match records with AWS Lake Formation FindMatches Visualize data with Amazon QuickSight Lab 3: Automate data lake creation using AWS Lake Formation blueprints Lab 4: Data visualization using Amazon QuickSight Module 6: Architecture and course review Post course knowledge check Architecture review Course review Additional course details: Nexus Humans Building Data Lakes on AWS training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Building Data Lakes on AWS course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours This course is intended for This course is intended for: Solutions architects and cloud architects seeking their AWS Certified Solutions Architect - Associate certification Customers and APN Partners who have 6 to 12 months of experience with AWS including a strong architecture background and experience Individuals who prefer an instructor led course for training and exam readiness Individuals who have not taken the Architecting on AWS course in the last ~6 months Overview In this course, you will learn to: Make architectural decisions based on AWS architectural principles and best practices Leverage AWS services to make your infrastructure scalable, reliable, and highly available Leverage AWS Managed Services to enable greater flexibility and resiliency in an infrastructure Make an AWS-based infrastructure more efficient to increase performance and reduce costs Use the Well-Architected Framework to improve architectures with AWS solutions Navigate the logistics of the examination process, exam structure, and question types Identify how questions relate to AWS architectural concepts Interpret the concepts being tested by an exam question This five-day, instructor-led course helps busy architects get away from the day-to-day to get focused and ready for their AWS Certified Solutions Architect ? Associate exam. Attendees learn the fundamentals of building IT infrastructure on AWS, so they can build scalable and resilient solutions in the cloud, by spending the first 3 days on the Architecting on AWS course. They?ll start getting in the exam readiness mindset with bonus end of module quizzes. Next, they?ll learn strategies to answer exam questions and avoid common mistakes with the Exam Readiness: AWS Certified Solutions Architect ? Associate half-day course. The course broadens attendees? knowledge of AWS services with deep dives into Amazon Redshift, Amazon Kinesis, and AWS Key Management Service, and then concludes with two quizzes and an instructor guided review of the AWS Certified Solutions Architect ? Associate practice exam. Architecting on AWS Module 1: Introduction Module 2: The Simplest Architectures Hands-On Lab 1: Hosting a Static Website Module 3: Adding a Compute Layer Module 4: Adding a Database Layer Hands-On Lab 2: Deploying a Web Application on AWS Module 5: Networking in AWS Part 1 Hands-On Lab 3: Creating a Virtual Private Cloud Architecting on AWS (continued) Module 6: Networking in AWS Part 2 Module 7: AWS Identity and Access Management (IAM) Module 8: Elasticity, High Availability, and Monitoring Hands-On Lab 4: Creating a Highly Available Environment Module 9: Automation Hands-On Lab 5: Automating Infrastructure Deployment with AWS CloudFormation Module 10: Caching Architecting on AWS (continued) Module 11: Building Decoupled Architectures Module 12: Microservices and Serverless Architectures Hands-On Lab 6: Implementing a Serverless Architecture with AWS Managed Services Module 13: RTP/RPO and Backup Recovery Setup Module 14: Optimizations and Review Exam Readiness: AWS Certified Solutions Architect -- Associate Module 0: The Exam Module 1: Design Resilient Architectures Module 2: Design Performant Architectures Module 3: Specify Secure Applications and Architectures Module 4: Design Cost-Optimized Architectures Module 5: Define Operationally Excellent Architectures Exam Readiness Additional deep dive of AWS services Quiz #1 Practice exam: AWS Certified Solutions Architect ? Associate Quiz #2 Wrap-up

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Developers responsible for developing Deep Learning applications Developers who want to understand concepts behind Deep Learning and how to implement a Deep Learning solution on AWS Overview This course is designed to teach you how to: Define machine learning (ML) and deep learning Identify the concepts in a deep learning ecosystem Use Amazon SageMaker and the MXNet programming framework for deep learning workloads Fit AWS solutions for deep learning deployments In this course, you?ll learn about AWS?s deep learning solutions, including scenarios where deep learning makes sense and how deep learning works. You?ll learn how to run deep learning models on the cloud using Amazon SageMaker and the MXNet framework. You?ll also learn to deploy your deep learning models using services like AWS Lambda while designing intelligent systems on AWS. Module 1: Machine learning overview A brief history of AI, ML, and DL The business importance of ML Common challenges in ML Different types of ML problems and tasks AI on AWS Module 2: Introduction to deep learning Introduction to DL The DL concepts A summary of how to train DL models on AWS Introduction to Amazon SageMaker Hands-on lab: Spinning up an Amazon SageMaker notebook instance and running a multi-layer perceptron neural network model Module 3: Introduction to Apache MXNet The motivation for and benefits of using MXNet and Gluon Important terms and APIs used in MXNet Convolutional neural networks (CNN) architecture Hands-on lab: Training a CNN on a CIFAR-10 dataset Module 4: ML and DL architectures on AWS AWS services for deploying DL models (AWS Lambda, AWS IoT Greengrass, Amazon ECS, AWS Elastic Beanstalk) Introduction to AWS AI services that are based on DL (Amazon Polly, Amazon Lex, Amazon Rekognition) Hands-on lab: Deploying a trained model for prediction on AWS Lambda Additional course details: Nexus Humans Deep Learning on AWS training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Deep Learning on AWS course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Intro to containers training course description This course looks at the technologies of containers and microservices. The course starts with a look at what containers are, moving onto working with containers. Networking containers and container orchestration is then studied. The course finishes with monitoring containers with Prometheus and other systems. Hands on sessions are used to reinforce the theory rather than teach specific products, although Docker and Kubernetes are used. What will you learn Use containers. Build containers. Orchestrate containers. Evaluate container technologies. Intro to containers training course details Who will benefit: Those wishing to work with containers. Prerequisites: Introduction to virtualization. Duration 2 days Intro to containers training course contents What are containers? Virtualization, VMs, What are containers? What are microservices? Machine containers, application containers. Benefits. Container runtime tools Docker, LXC, Windows containers. Architecture, components. Hands on Installing Docker client and server. Working with containers Docker workflow, Docker images, Docker containers, Dockerfile, Building, running, storing images. Creating containers. Starting, stopping and controlling containers. Public repositories, private registries. Hands on Exploring containers. Microservices What are microservices? Modular architecture, IPC. Hands on Persistence and containers. Networking containers Linking, no networking, host, bridge. The container Network Interface. Hands on Container networking Container orchestration engines Docker swarm: Nodes, services, tasks. Apache Mesos: Mesos master, agents, frameworks. Kubernetes: Kubectl, master node, worker nodes. Openstack: Architecture, containers in OpenStack. Amazon ECS: Architecture, how it works. Hands on Setup and access a Kubernetes cluster. Managing containers Monitoring, logging, collecting metrics, cluster monitoring tools: Heapster. Hands on Using Prometheus with Kubernetes.

Docker for engineers training course description Docker is the container platform of choice. This course covers how to use Docker to package your applications with all of their dependencies and then test, deploy, scale and support your containers. Hands on sessions follow all the major sessions. What will you learn Work with Docker images, containers and command line tools. Deploy and test Docker containers. Debug Docker containers. Describe Docker networking, deployment tools, orchestration and security. Docker for engineers training course details Who will benefit: Anyone working with Docker. Prerequisites: Introduction to virtualization. Duration 2 days Docker for engineers training course contents Introduction The birth of Docker, the promise of Docker, what Docker isn't. Docker at a glance Process simplification, broad support and adoption, architecture, getting the most from Docker, the Docker workflow. Installing Docker Important terminology, Docker client, Docker server, test the setup. Working with Docker images Anatomy of a Dockerfile, building an image, running your image, custom base images, storing images. Working with Docker containers What are containers? creating a container, starting a container, auto-restarting a container, stopping a container, killing a container, pausing and unpausing a container, cleaning up containers and images, next steps. Exploring Docker Printing the Docker version, server information, downloading image updates, inspecting a container, getting inside a running container, exploring the shell, returning a result, docker logs, monitoring Docker, exploration. The path to production containers Deploying, testing containers. Debugging containers Process output, process inspection, controlling processes, network inspection, image history, inspecting a container, filesystem inspection, moving along. Docker at scale Docker swarm, centurion, amazon EC2 container service. Advanced topics Pluggable backends, containers in detail, security, networking. Designing your production container platform The twelve-factor app, the reactive manifesto. Conclusion The challenges, the Docker workflow, minimizing deployment artifacts, optimizing storage and retrieval, the payoff, the final word.

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: Solutions Architects and Engineers who perform cloud migrations IT Project Managers who are involved in projects related to migrating existing workloads to the AWS Cloud Overview This course is designed to teach you how to: Explain the various cloud migration strategies Assess cloud migration readiness Discover your portfolio and plan for migration Plan and design your application migration strategy Perform and validate application migration to the cloud Optimize your applications and operations after migrating to the cloud Migrating to AWS focuses on planning and migrating existing workloads to the AWS Cloud. The course covers various cloud migration strategies with a detailed discussion on each phase of the migration process, including portfolio discovery, application migration planning and design, migration execution, and post-migration validation and application optimization. This course is designed for Solutions Architects and Engineers who perform cloud migrations, have an understanding of core AWS services and design patterns covered in Architecting on AWS. This course is also available to IT project managers involved in the planning of those migrations who have completed AWS Technical Essentials Module 1: Migrating to AWS ? Overview Migration process 'Mental Model' Cloud Migration Strategies Comparing Cloud Migration Strategies Cloud Center of Excellence (CoE) Cloud Migration Readiness Assessment AWS Cloud Migration Process Group activity: Creating a high-level migration plan Module 2: Discovery and analysis Migration Process Roadmap AWS Migration Methodology AWS Application Discovery Service Portfolio Analysis Hands-on lab 1: Performing discovery Module 3: Migration planning and design (part I) AWS Migration Hub Pricing and Availability Process Group activity: Creating a detailed migration plan Module 3: Migration planning and design (continued) Application migration ordering Application prioritization criteria Defining success criteria Migration methodology Designing for migration Module 4: Migration, integration, and validation Migration considerations Data migration AWS Snow Services AWS Data Migration Service (DMS) Server migration Demonstration: Server migration service Hands-on lab 2 : Migrating databases to AWS EC2 Hands-on lab 3 : Migrating databases to Amazon Aurora Module 5: Operations and optimization On premises vs. cloud IT operations Optimizing in the AWS Cloud Case study: Optimizing an application

Unconscious bias from a fresh new perspective for anyone who interacts with, or makes decisions about, people; whether you work with customers, supervise staff or work in collaboration, this session will enhance your insight and interactions.