Online or onsite, instructor-led live AWS (Amazon Web Services) training courses demonstrate through interactive hands-on practice the fundamentals and advanced concepts of AWS.
AWS training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Amazon Web Services (AWS) training can be carried out locally on customer premises in Dartmouth or in NobleProg corporate training centers in Dartmouth.
NobleProg -- Your Local Training Provider
Dartmouth - Metropolitan Place
99 Wyse Road, Dartmouth, Canada, B3A 4S5
Metropolitan Place is an ocean-front building, close to Alderney Landing and home to leading businesses. Motorway exits and the local ferry terminal are located close by, and restaurants cafes are easily accessible for lunch.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at intermediate-level IT professionals who wish to learn how to leverage AWS tools and services to build, train, and deploy AI models efficiently.
By the end of this training, participants will be able to:
Understand the AI/ML services provided by AWS.
Be able to set up and manage AI/ML environments on AWS.
Gain hands-on experience in building, training, and deploying AI models using Amazon SageMaker.
Learn to utilize various AWS AI services for specific use cases.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at advanced-level cloud professionals who wish to master cloud infrastructure management and automation using AWS Cloud9 and AWS CDK.
By the end of this training, participants will be able to:
Set up and configure AWS Cloud9 for infrastructure management.
Understand and apply AWS CDK to automate cloud resource provisioning.
Design efficient and scalable cloud infrastructure solutions.
Optimize cloud resources to improve performance and reduce costs.
Implement advanced security and compliance strategies in AWS infrastructure.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at intermediate-level developers who wish to master building and deploying microservices with AWS Cloud9 and other AWS services.
By the end of this training, participants will be able to:
Understand microservices architecture and its benefits.
Set up a microservices development environment on AWS Cloud9.
Build, test, and deploy microservices using Docker and AWS services.
Integrate AWS Lambda, ECS, and API Gateway with microservices.
Apply DevOps practices to manage microservices deployments.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at intermediate-level data scientists and analysts who wish to use AWS Cloud9 for streamlined data science workflows.
By the end of this training, participants will be able to:
Set up a data science environment in AWS Cloud9.
Perform data analysis using Python, R, and Jupyter Notebook in Cloud9.
Integrate AWS Cloud9 with AWS data services like S3, RDS, and Redshift.
Utilize AWS Cloud9 for machine learning model development and deployment.
Optimize cloud-based workflows for data analysis and processing.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at intermediate-level to advanced-level full-stack developers who wish to utilize AWS Cloud9 to streamline their development workflows.
By the end of this training, participants will be able to:
Set up and configure AWS Cloud9 for full-stack development.
Develop and debug front-end applications using Cloud9.
Build and deploy back-end services using AWS Cloud9.
Integrate Cloud9 with AWS services for advanced deployments.
Collaborate with team members in a cloud-based development environment.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at intermediate-level Python developers who wish to enhance their Python development experience using AWS Cloud9.
By the end of this training, participants will be able to:
Set up and configure AWS Cloud9 for Python development.
Understand the AWS Cloud9 IDE interface and features.
Write, debug, and deploy Python applications in AWS Cloud9.
Collaborate with other developers using the AWS Cloud9 platform.
Integrate AWS Cloud9 with other AWS services for advanced deployments.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at beginner-level developers who wish to set up and use AWS Cloud9 for cloud-based projects.
By the end of this training, participants will be able to:
Understand the AWS Cloud9 environment and its components.
Set up their own AWS Cloud9 development workspace.
Develop and run simple applications within AWS Cloud9.
Familiarize themselves with the collaboration features of AWS Cloud9.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at beginner-level to intermediate-level system administrators and IT professionals who wish to gain hands-on experience in managing AWS cloud services and prepare for the AWS Certified SysOps Administrator - Associate exam.
By the end of this training, participants will be able to:
Set up and configure AWS services and resources securely.
Manage user identities, permissions, and access to AWS resources.
Design and deploy scalable, highly available, and fault-tolerant systems on AWS.
Implement and manage data flow to and from AWS.
Optimize AWS service usage to ensure efficient operation and cost management.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at beginner-level to intermediate-level IT professionals who wish to learn how to conduct an AWS security audit effectively and efficiently.
By the end of this training, participants will be able to:
Understand the core concepts and benefits of AWS security audit.
Use AWS tools and services to perform an AWS security audit.
Analyze and interpret the audit results and recommendations.
Implement the audit findings and remediate the issues.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at intermediate-level cloud architects and developers who wish to gain the knowledge and tools necessary to efficiently manage and optimize AWS costs, aligning cloud spending with business objectives.
By the end of this training, participants will be able to:
Understand how AWS pricing works and how different services contribute to overall costs.
Learn how to implement cost-saving measures, utilize reserved instances, and optimize resource usage.
Develop skills to create, manage, and adhere to budgets within the AWS framework.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at beginner to intermediate-level IT professionals who wish to gain the knowledge and skills required to secure Amazon Web Services (AWS) environments effectively.
By the end of this training, participants will be able to:
Understand the core concepts of AWS Cloud Security and its importance in a cloud environment.
Implement effective access controls, authentication mechanisms, and multi-factor authentication to secure AWS resources.
Define and enforce security policies and monitor AWS resources.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of DevOps practices and streamline development processes using AWS Cloud9.
By the end of this training, participants will be able to:
Set up and configure AWS Cloud9 for DevOps workflows.
Implement continuous integration and continuous delivery (CI/CD) pipelines.
Automate testing, monitoring, and deployment processes using AWS Cloud9.
Integrate AWS services such as Lambda, EC2, and S3 into DevOps workflows.
Utilize source control systems like GitHub or GitLab within AWS Cloud9.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at developers who wish to build serverless applications using services in the AWS serverless platform.
By the end of this training, participants will be able to:
Implement event-driven best practices in designing serverless applications using appropriate AWS services.
Build serverless applications using AWS services.
Monitor, secure, and scale serverless applications on AWS.
Utilize different developer tools to configure and automate serverless application deployment.
Create and maintain a list of serverless resources that will aid in serverless application development.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at intermediate-level professionals who wish to learn how to effectively build, deploy, and maintain serverless applications on AWS Cloud9 and AWS Lambda.
By the end of this training, participants will be able to:
Understand the fundamentals of serverless architecture.
Set up AWS Cloud9 for serverless application development.
Develop, test, and deploy serverless applications using AWS Lambda.
Integrate AWS Lambda with other AWS services such as API Gateway and S3.
Optimize serverless applications for performance and cost efficiency.
EKS is a self-managed Kubernetes-as-a-service offering from AWS. EKS is fully scalable and customizable and allows a Kubernetes deployment to mimic and/or integrate with an existing on-premise Kubernetes setup.
In this instructor-led, live training, participants will learn how to set up and manage a production-scale container environment using Kubernetes on EKS.
By the end of this training, participants will be able to:
Configure and manage Kubernetes on EKS
Migrate an existing Kubernetes environment from on-premise to AWS cloud
Integrate Kubernetes with third-party continuous integration (CI) software
Ensure high availability and disaster recovery in Kubernetes
Understand and adopt the tools available to efficiently manage EKS
Audience
Developers
System Administrators
DevOps Engineers
Format of the Course
Part lecture, part discussion, exercises and heavy hands-on practice in a live-lab environment.
Note
To request a customized training for this course, please contact us to arrange.
This instructor-led, live training in (online or onsite) is aimed at engineers who wish to evaluate each of these services to make an informed decisions about which to deploy within their organization.
By the end of this training, participants will be able to:
Set up a development environment that includes all needed libraries, packages and frameworks needed to start developing.
Set up, configure and deploy a series of demo containers using a number of different approaches.
Understand the architectural and design differences among different Docker/Kubernetes solutions within AWS.
Automate the deployment of Docker containers.
Set up a continuous integration and deployment pipeline.
Integrate Docker and Kubernetes into an existing continuous integration system.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at cloud engineers and developers who wish to use CloudFormation to manage infrastructure resources within the AWS ecosystem.
By the end of this training, participants will be able to:
Implement CloudFormation templates to automate infrastructure management.
Integrate existing AWS resources into CloudFormation.
Use StackSets to manage stacks across multiple accounts and regions.
Amazon Redshift is a petabyte-scale cloud-based data warehouse service in AWS.
In this instructor-led, live training, participants will learn the fundamentals of Amazon Redshift.
By the end of this training, participants will be able to:
Install and configure Amazon Redshift
Load, configure, deploy, query, and visualize data with Amazon Redshift
Audience
Developers
IT Professionals
Format of the course
Part lecture, part discussion, exercises and heavy hands-on practice
Note
To request a customized training for this course, please contact us to arrange.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at developers who wish to use Amazon S3 to enable cloud-based storage for their websites, web applications and/or mobile applications.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at cloud engineers wishing to understand and implement the more complex aspects of AWS architecture. The course covers many of the same topics as the AWS Certified Solutions Architect (Professional) level courses. However, this course is NOT intended to prepare participants to take an exam. This is a hands-on, practical course that demonstrates how to implement in a live lab environment many of the configurations, implementations, and deployments that an AWS Solutions Architect would need to carry out.
By the end of this training, participants will be able to:
Design complex cloud solutions on AWS.
Deploy software applications on AWS that are scalable, highly available, and fault-tolerant.
Integrate the most appropriate AWS services with an application.
Migrate a complex software application to AWS.
Apply best practices to the design, implementation, optimization and deployment of infrastructure and applications on AWS.
On demand AWS Architect Certification training course is designed to help professionals to become cloud-enabled using Amazon Web Services. This course is taught with real life examples, helps participants understand the practical application of concepts such as fundamentals of cloud computing, Amazon Web services (AWS), Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), Private Clouds and Cloud programming. After this course participants will be able to have their own implementations on cloud using EC2 instances, S3 buckets etc.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at DevOps engineers and developers who wish to use CodePipeline to automate release pipelines for efficient updating of applications and infrastructures.
By the end of this training, participants will be able to use CodePipeline features and tools to automate and configure workflows in software release workflows.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at developers who wish to integrate a DynamoDB NoSQL database into a web application hosted on AWS.
By the end of this training, participants will be able to:
Set up the necessary development environment to start integrating data into DynamoDB.
Integrate DynamoDB into web applications and mobile applications.
Audience:
Cloud engineers, Solution architects, Centre of excellence team, Window server administrators, Unix/Linux administrator, Storage administrators, network administrators, Virtualization administrators
Course Objectives:
This course is designed to teach you how to:
Use the principal concepts and practices behind the DevOps methodology
Design and implement an infrastructure on AWS that supports one or more DevOps development projects
Use AWS CloudFormation and AWS OpsWorks to deploy the infrastructure necessary to create development, test, and production environments for a software development project
Use AWS CodeCommit and understand the array of options for enabling a Continuous Integration environment on AWS
Use AWS CodePipeline to design and implement a Continuous Integration and Delivery pipeline on AWS
Implement several common Continuous Deployment use cases using AWS technologies, including blue/green deployment and A/B testing
Distinguish between the array of application deployment technologies available on AWS (including AWS CodeDeploy, AWS Opsworks, AWS Elastic Beanstalk, Amazon EC2 Container Service, and Amazon EC2 Container Registry), and decide which technology best fits a given scenario
Fine tune the applications you deliver on AWS for high performance and use AWS tools and technologies to monitor your application and environment for potential issues
An understanding of the Core AWS services, uses, and basic architecture best practices.
Proficiency in designing, developing, and deploying cloud-based solutions using AWS.
Experience with developing and maintaining applications written for Amazon Simple Storage Service, Amazon DynamoDB, Amazon Simple Queue Service, Amazon Simple Notification Service, Amazon Simple Workflow Service, AWS Elastic Beanstalk, and AWS CloudFormation.
Audience:
Cloud engineers, Centre of excellence team, Window server administrators, Unix/Linux administrator, Storage administrators, Network administrators , Virtualization administrators.
On Completion of this training programme participants should able to deploy and use AWS services from a Developer standpoint.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at engineers who wish to use Amazon ECS to deploying and scaling containerized applications.
By the end of this training, participants will be able to:
Create a containerized application running on Amazon ECS.
Understand how ECS Clusters and the ECS Agent work.
Auto Scale a Containerized Application
Automate the Deployment Process
Integrate the Docker application deployment process with new or existing Continuous Integration workflows.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at engineers who wish to use Amazon EKS to deploy and scale containerized applications across AWS managed Kubernetes clusters.
By the end of this training, participants will be able to:
Set up an EKS based Kubernetes cluster.
Create and run a containerized application on Amazon EKS.
Auto-scale a Containerized Application
Automate the Deployment Process
Integrate EKS based applications with a new or existing Continuous Integration workflow.
This instructor-led, live training in Dartmouth (onsite or remote) is aimed at engineers who wish to deploy and manage IoT devices on AWS.
By the end of this training, participants will be able to build an IoT platform that includes the deployment and management of a backend, gateway, and devices on top of AWS.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at developers who wish to install, configure, and manage AWS IoT Greengrass capabilities to create applications for various devices.
By the end of this training, participants will be able to use AWS IoT Greengrass to build, deploy, manage, secure, and monitor applications on intelligent devices.
This instructor-led, live training in Dartmouth (onsite or remote) is aimed at developers who wish to use AWS Lambda to build and deploy services and applications to the cloud, without needing to worry about provisioning the execution environment (servers, VMs and containers, availability, scalability, storage, etc.).
By the end of this training, participants will be able to:
Configure AWS Lambda to execute a function.
Understand FaaS (Functions as a Service) and the advantages of serverless development.
Build, upload and execute AWS Lambda functions.
Integrate Lambda functions with different event sources.
Package, deploy, monitor and troubleshoot Lambda based applications.
This instructor-led, live training in Dartmouth provides an overview of AWS products, services and solutions. It is aimed at individuals and teams who are:
evaluating/preparing for an initial deployment of their IT infrastructure on AWS.
evaluating/preparing to migrate their existing IT infrastructure to the AWS public cloud.
By the end of this training, participants will have a clear understanding of the principal components that make up Amazon's cloud offering. The hands-on exercises, discussions and in-class deployments will provide participants with the practice and feedback they need to feel comfortable and prepared to carry out their own live deployments to AWS.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at developers who wish to install, configure, and manage AWS RoboMaker capabilities to create, simulate, and deploy applications for robots and autonomous vehicles and devices.
By the end of this training, participants will be able to use AWS RoboMaker to build, simulate, deploy, manage, test, and monitor robot applications.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at data scientists and developers who wish to create and train machine learning models for deployment into production-ready hosting environments.
By the end of this training, participants will be able to:
Use notebook instances to prepare and upload data for training.
Train machine learning models using training datasets.
Deploy trained models to an endpoint to create predictions.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at technical persons who wish to understand AWS products and services so as to make an informed decision about how to implement AWS cloud solutions within their organization.
By the end of this training, participants will be able to:
Identify and understand the role of each of the services offered by AWS.
Understand the terminology and concepts related to AWS.
Navigate the AWS Management Console.
Set up and manage team user accounts securely.
Match AWS's services to an organization's problem and requirements.
Make informed decisions about which AWS services to implement.
Plan out a broad cloud solution strategy for an organization.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at engineers who wish to use AWS CloudFormation to automate the process of managing AWS cloud infrastructure.
By the end of this training, participants will be able to:
Enable AWS services to get started managing infrastructure.
Understand and apply the principle of "infrastructure as code".
Improve quality and lower the costs of deploying infrastructure.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at engineers who wish to deploy Machine Learning workloads to an AWS EC2 server.
By the end of this training, participants will be able to:
Install and configure Kubernetes, Kubeflow and other needed software on AWS.
Use EKS (Elastic Kubernetes Service) to simplify the work of initializing a Kubernetes cluster on AWS.
Create and deploy a Kubernetes pipeline for automating and managing ML models in production.
Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel.
Leverage other AWS managed services to extend an ML application.
This instructor-led, live training in (online or onsite) is aimed at engineers who wish to use Terraform on AWS to plan and build cloud infrastructure.
By the end of this training, participants will be able to:
Install and configure Terraform on AWS.
Implement an "infrastructure as code" approach to managing AWS cloud environments.
Create, launch, and dismantle infrastructure from within a single tool.
Write declarative configuration files that can be managed like any other source code in a version control system.
Quickly update configuration files for effectively responding to changing compute resource needs.
Collaborate with other infrastructure engineers by sharing configuration files in a common code repository.
Improve transparency in the infrastructure procurement process.
“Things”, “Sensors”, Internet and the mapping between business functions of IoT
Essential of all IoT software components- hardware, firmware, middleware, cloud and mobile app
IoT functions- Fleet manager, Data visualization, SaaS based FM and DV, alert/alarm, sensor onboarding, “thing” onboarding, geo-fencing
Basics of IoT device communication with cloud with MQTT.
Connecting IoT devices to AWS with MQTT (AWS IoT Core).
Connecting AWS IoT core with AWS Lambda function for computation and data storage.
Connecting Raspberry PI with AWS IoT core and simple data communication.
Alerts and events
Sensor calibration
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Testimonials (11)
Trainer had good grasp of concepts
Josheel - Verizon Connect
Course - Amazon Redshift
The practice part.
Radu - Ness Digital Engineering
Course - AWS: A Hands-on Introduction to Cloud Computing
Into class that dove deeper than expected into the material. While I am not proficient in the subject matter, I am now equipped with an awareness of how the process works.
Jon - U.S. Geological Survey
Course - AWS Technical Essentials
The quality of the explanations, and the large number of topics covered
Hugo SECHIER - Expleo France
Course - Kubeflow on AWS
Machine Translated
The training was more practical
Siphokazi Biyana - Vodacom SA
Course - Kubernetes on AWS
The trainer knew exactly what they were speaking about.
Madumetsa Msomi - BMW
Course - AWS DevOps Engineers
There were lots of hands on examples and the walkthroughs we carefully explained.
Jeffrey Ronay - Federal Reserve Bank of SF
Course - Terraform on AWS
All good, nothing to improve
Ievgen Vinchyk - GE Medical Systems Polska Sp. Z O.O.
Course - AWS Lambda for Developers
IOT applications
Palaniswamy Suresh Kumar - Makers' Academy
Course - Industrial Training IoT (Internet of Things) with Raspberry PI and AWS IoT Core 「4 Hours Remote」
I liked getting to understand the breadth of the services offered by AWS and gaining a better understanding of their pricing model for each of those services.
William Crowdis - MDA Systems Ltd.
Course - AWS Developer Associate
Gabriel was very organized and prepared for this training. He answered all questions and clarify the AWS notions and architecture. Great job, Gabriel.
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