27 AWS Lambda courses delivered Online

Learn how you can develop and deploy Java, Python, NodeJS Lambda Functions and manage them using Python and Boto3!

You will learn how to develop reliable and scalable serverless applications, following the microservices architecture. We will develop event-driven microservices with AWS serverless services that come with the power of the cloud, high availability and high scalability by nature following serverless design patterns and best practices.

Do you want to build a simple, reliable, and error-free chatbot for your business? If yes, then this is the course for you! Learn to build a chatbot with Amazon Lex, a fully-controlled AI service with sophisticated natural language models to create, develop, test, and deploy chatbots (conversational interfaces) in applications.

This course is focused on concepts of Python Boto3 Module and Lambda using Python. It covers how to use Boto3 module, concepts of Boto3 (session, resource, client, meta, collections, waiters, and paginators), and AWS Lambda to build real-time tasks with lots of step-by-step examples.

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: Intermediate software developers Overview In this course, you will learn to: Set up the AWS SDK and developer credentials for Java, C#/.NET, Python, and JavaScript Interact with AWS services and develop solutions by using the AWS SDK Use AWS Identity and Access Management (IAM) for service authentication Use Amazon Simple Storage Service (Amazon S3) and Amazon DynamoDB as data stores Integrate applications and data by using AWS Lambda, Amazon API Gateway, Amazon Simple Queue Service (Amazon SQS), Amazon Simple Notification Service (Amazon SNS), and AWS Step Functions Use Amazon Cognito for user authentication Use Amazon ElastiCache to improve application scalability Leverage the CI/CD pipeline to deploy applications on AWS In this course, you learn how to use the AWS SDK to develop secure and scalable cloud applications using multiple AWS services such as Amazon DynamoDB, Amazon Simple Storage Service, and AWS Lambda. You explore how to interact with AWS using code and learn about key concepts, best practices, and troubleshooting tips. Module 0: Course Overview Agenda Introductions Student resources Module 1: Introduction to AWS Introduction to the AWS Cloud Cloud scenarios Infrastructure overview Introduction to AWS foundation services Module 2: Introduction to Developing on AWS Getting started with developing on AWS Introduction to developer tools Introduction to management tools Module 3: Introduction to AWS Identity and Access Management Shared responsibility model Introduction to IAM Use authentication and authorization Module 4: Introduction to the Lab Environment Introduction to the lab environment Lab 1: Getting started and working with IAM Module 5: Developing Storage Solutions with Amazon Simple Storage Service Overview of AWS storage options Amazon S3 key concepts Best practices Troubleshooting Scenario: Building a complete application Lab 2: Developing storage solutions with Amazon S3 Module 6: Developing Flexible NoSQL Solutions with Amazon DynamoDB Introduction to AWS database options Introduction to Amazon DynamoDB Developing with DynamoDB Best practices Troubleshooting Scenario: Building an end-to-end app Lab 3: Developing flexible NoSQL solutions with Amazon DynamoDB Module 7: Developing Event-Driven Solutions with AWS Lambda What is serverless computing? Introduction to AWS Lambda Key concepts How Lambda works Use cases Best practices Scenario: Build an end-to-end app Module 8: Developing Solutions with Amazon API Gateway Introduction to Amazon API Gateway Developing with API Gateway Best practices Introduction to AWS Serverless Application Model Scenario: Building an end-to-end app Lab 4: Developing event-driven solutions with AWS Lambda Module 9: Developing Solutions with AWS Step Functions Understanding the need for Step Functions Introduction to AWS Step Functions Use cases Module 10: Developing Solutions with Amazon Simple Queue Service and Amazon Simple Notification Service Why use a queueing service? Developing with Amazon Simple Queue Service Developing with Amazon Simple Notification Service Developing with Amazon MQ Lab 5: Developing messaging solutions with Amazon SQS and Amazon SNS Module 11: Caching Information with Amazon ElastiCache Caching overview Caching with Amazon ElastiCache Caching strategies Module 12: Developing Secure Applications Securing your applications Authenticating your applications to AWS Authenticating your customers Scenario: Building an end-to-end app Module 13: Deploying Applications Introduction to DevOps Introduction to deployment and testing strategies Deploying applications with AWS Elastic Beanstalk Scenario: Building an end-to-end app Lab 6: Building an end-to-end app Module 14: Course wrap-up Course overview AWS training courses Certifications Course feedback

The complete manual to help you master real-world AWS concepts and pass the AWS Developer Associate - Exam

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.

This course helps you to understand the concepts of the AWS Cloud and covers all the fundamental topics of AWS, such as core services, security essentials, architecting essentials, and pricing essentials.

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 3 Days 18 CPD hours This course is intended for This course is intended for security engineers, security architects, and information security professionals. Overview Identify security benefits and responsibilities of using the AWS Cloud Build secure application infrastructures Protect applications and data from common security threats Perform and automate security checks Configure authentication and permissions for applications and resources Monitor AWS resources and respond to incidents Capture and process logs Create and configure automated and repeatable deployments with tools such as AMIs and AWS CloudFormation This course demonstrates how to efficiently use AWS security services to stay secure in the AWS Cloud. The course focuses on the security practices that AWS recommends for enhancing the security of your data and systems in the cloud. The course highlights the security features of AWS key services including compute, storage, networking, and database services. You will also learn how to leverage AWS services and tools for automation, continuous monitoring and logging, and responding to security incidents. Prerequisites We recommend that attendees of this course have: Working knowledge of IT security practices and infrastructure concepts Familiarity with cloud computing concepts Completed AWS Security Essentials and Architecting on AWS courses 1 - Security on AWS Security in the AWS cloud AWS Shared Responsibility Model Incident response overview DevOps with Security Engineering 2 - Identifying Entry Points on AWS Identify the different ways to access the AWS platform Understanding IAM policies IAM Permissions Boundary IAM Access Analyzer Multi-factor authentication AWS CloudTrail 3 - Security Considerations: Web Application Environments Threats in a three-tier architecture Common threats: user access Common threats: data access AWS Trusted Advisor 4 - Application Security Amazon Machine Images Amazon Inspector AWS Systems Manager 5 - Data Security Data protection strategies Encryption on AWS Protecting data at rest with Amazon S3, Amazon RDS, Amazon DynamoDB Protecting archived data with Amazon S3 Glacier Amazon S3 Access Analyzer Amazon S3 Access Points 6 - Securing Network Communications Amazon VPC security considerations Amazon VPC Traffic Mirroring Responding to compromised instances Elastic Load Balancing AWS Certificate Manager 7 - Monitoring and Collecting Logs on AWS Amazon CloudWatch and CloudWatch Logs AWS Config Amazon Macie Amazon VPC Flow Logs Amazon S3 Server Access Logs ELB Access Logs 8 - Processing Logs on AWS Amazon Kinesis Amazon Athena 9 - Security Considerations: Hybrid Environments AWS Site-to-Site and Client VPN connections AWS Direct Connect AWS Transit Gateway 10 - Out-Of-Region Protection Amazon Route 53 AWS WAF Amazon CloudFront AWS Shield AWS Firewall Manager DDoS mitigation on AWS 11 - Security Considerations: Serverless Environments Amazon Cognito Amazon API Gateway AWS Lambda 12 - Threat Detection and Investigation Amazon GuardDuty AWS Security Hub Amazon Detective 13 - Secrets Management on AWS AWS KMS AWS CloudHSM AWS Secrets Manager 14 - Automation and Security by Design AWS CloudFormation AWS Service Catalog 15 - Account Management and Provisioning on AWS AWS Organizations AWS Control Tower AWS SSO AWS Directory Service