Querétaro - Milenio III

Sendero del Mirador 36 Milenio III, Querétaro, mexico, 76060
Classrooms are located in a new district, 5 minute walk from restaurants, cafes and shops.

Subcategories (4)

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AWS IoT
Image for AWS Lambda category
AWS Lambda
Image for CloudFormation category
CloudFormation
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Amazon DynamoDB

Explore Our Courses

AWS Cloud Administrator Certification

 35 Hours
This instructor-led, live training in Queretaro (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.
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AWS Security Audit

 21 Hours
This instructor-led, live training in Queretaro (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.
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AWS Financial Management for Builders

 21 Hours
This instructor-led, live training in Queretaro (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.
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AWS Cloud Security

 21 Hours
This instructor-led, live training in Queretaro (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.
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Developing Serverless Solutions on AWS

 21 Hours
This instructor-led, live training in Queretaro (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.
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Kubernetes on AWS

 14 Hours
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.
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Docker and Kubernetes on AWS

 21 Hours
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.
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Amazon Redshift

 21 Hours
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.
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Amazon S3 Fundamentals

 14 Hours
This instructor-led, live training in Queretaro (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.
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AWS Advanced Architecture

 28 Hours
This instructor-led, live training in Queretaro (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.
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AWS Architect Certification

 21 Hours
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.
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Amazon Web Services (AWS) CodePipeline

 7 Hours
This instructor-led, live training in Queretaro (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.
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AWS DevOps Engineers

 21 Hours
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
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AWS Developer Associate

 28 Hours
This 4 day course will provide: 
  • 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.
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Amazon ECS (AWS ECS)

 14 Hours
This instructor-led, live training in Queretaro (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.
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Amazon EKS (AWS EKS)

 14 Hours
This instructor-led, live training in Queretaro (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.
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Core Hybrid Cloud Functionalities with AWS Outposts

 21 Hours
This instructor-led, live training in Queretaro (online or onsite) is aimed at engineers, developers, and administrative IT personnel who wish to optimize their organization's data center and workflows using the fully supported system of AWS Outposts. By the end of this training, participants will be able to:
  • Evaluate and prepare the on-premise environment for AWS Outposts setup and installation.
  • Configure an Outpost based on the suitable memory and storage options for the enterprise.
  • Adjust to AWS cloud architecture and familiarize with the interface of AWS Outposts.
  • Utilize the primary tools and features of an Outpost for big data processing and development implementations.
  • Execute more flexible and seamless management methods within the organization.
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AWS: A Hands-on Introduction to Cloud Computing

 7 Hours
This instructor-led, live training in Queretaro 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.
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Amazon Web Services (AWS) RoboMaker

 21 Hours
This instructor-led, live training in Queretaro (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.
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Amazon Web Services (AWS) SageMaker

 21 Hours
This instructor-led, live training in Queretaro (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.
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AWS Technical Essentials

 7 Hours
This instructor-led, live training in Queretaro (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.
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Creating a CDN with Amazon CloudFront

 14 Hours
This instructor-led, live training in Queretaro (online or onsite) is aimed at engineers who wish to accelerate the performance of their website or web application by way of an Amazon CloudFront CDN (content delivery network). By the end of this training, participants will be able to:
  • Setup the appropriate AWS account to access CloudFront.
  • Cache media content such as video and audio near consumers to reduce latency and increase download speed.
  • Cache frequently accessed static content such as website images and downloadable software.
  • Cache dynamic, streaming, and interactive content to improve the customer experience.
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Kubeflow on AWS

 28 Hours
This instructor-led, live training in Queretaro (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.
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Terraform on AWS

 21 Hours
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.
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Advanced AWS Lambda

 14 Hours
This instructor-led, live training in Queretaro (online or onsite) is aimed at developers who wish to integrate AWS Lambda applications and services with other services (API Gateway, Kinesis Streams, etc.). The training demonstrates how to use the browser-based AWS Cloud9 IDE to develop software collaboratively.   By the end of this training, participants will be able to:
  • Collaboratively develop functions, applications and services using AWS Cloud9 IDE.
  • Integrate AWS Lambda functions with other AWS services.
  • Create and manage APIs.
  • Set up an AWS Lambda function to read and process real-time streaming data.
  • Create and manage a continuous integration pipeline for building, testing and deploying a AWS Lambda functions and applications.
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AWS Lambda for Developers

 14 Hours
This instructor-led, live training in Queretaro (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.
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AWS IoT Core

 14 Hours
This instructor-led, live training in Queretaro (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.
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Amazon Web Services (AWS) IoT Greengrass

 21 Hours
This instructor-led, live training in Queretaro (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.
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Industrial Training IoT (Internet of Things) with Raspberry PI and AWS IoT Core 「8 Hours Remote」

 8 Hours
Summary:
  • Basics of IoT architecture and functions
  • “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 using DynamoDB.
  • Connecting Raspberry PI with AWS IoT core and simple data communication.
  • Hands on with Raspberry PI and AWS IoT Core to build a smart device.
  • Sensor data visualization and communication with web interface.
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Industrial Training IoT (Internet of Things) with Raspberry PI and AWS IoT Core 「4 Hours Remote」

 4 Hours
Summery:
  • Basics of IoT architecture and functions
  • “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 (10)

The general topic itself

- Verizon Connect
Course - Amazon Redshift

The trainer is very well prepared, you have enough time to finish each assignment. Among the best trainings I have attended.

Ana - Ness Digital Engineering
Course - AWS Technical Essentials

I liked how well organized the trainer was and also how well the material was structured and presented.

Ana - Ness Digital Engineering
Course - AWS: A Hands-on Introduction to Cloud Computing

It's a pity that some time was lost due to problems with virt machines on day 1.

Przemek - EduBroker Sp z oo

Machine Translated

The docker ready-to-use environment image. The balance between lectures and exercises.

Aurélien Petit - Prostep sp. z o. o.
Course - AWS DevOps Engineers

Sounds knowledgeable, and interacts with his leaners

Shuko Ndhlovu - BMW
Course - AWS Developer Associate

Concepts learnt and how to set up the k8 clusters

Sekgwa Ramatshosa - Vodacom SA
Course - Kubernetes on AWS

Free atmosphere and agenda flexibility

Marcin Prewo - 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」

Showing the different features of AWS and help the audience in case something doesn't work properly.

Issam IEBOUBEN - HSBC Service Delivery (Polska) Sp. z o o.
Course - AWS Architect Certification

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