Azure Training in Medellín

This instructor-led, live training in Medellín (online or onsite) is aimed at intermediate-level Java developers, software engineers, and cloud enthusiasts who wish to harness the power of Azure OpenAI to create intelligent applications.

By the end of this training, participants will be able to:

• Understand the principles of Generative AI and its applications.
• Set up and manage an Azure OpenAI service.
• Integrate OpenAI's models into Java applications.
• Deploy AI-powered features within web applications.

This instructor-led, live training in Medellín (online or onsite) is aimed at intermediate-level cloud engineers and IT professionals who wish to use Terraform to automate the deployment, management, and scaling of infrastructure on the Azure cloud platform.

By the end of this training, participants will be able to:

• Understand the basics of Terraform and its benefits in infrastructure as code.
• Set up and configure Terraform for Azure.
• Develop, test, and deploy Terraform configuration files for various Azure services.
• Use Terraform for managing and scaling Azure resources.
• Implement best practices for Terraform state management and version control.
• Integrate Terraform with Azure DevOps for automated deployments.
• Create reusable Terraform modules for consistent resource provisioning.
• Utilize advanced features of Terraform for complex infrastructure deployments.

This instructor-led, live training in Medellín (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to build and deploy AI-powered cloud applications using Microsoft Azure.

By the end of this training, participants will be able to:

• Develop event-driven and serverless applications using Azure Functions.
• Manage Azure storage solutions and virtual machines.
• Deploy and scale web applications using Azure App Service and Docker containers.
• Integrate AI, machine learning, and natural language processing using Azure AI Services.
• Leverage GitHub Copilot to assist in AI-driven cloud application development.

This instructor-led, live training in Medellín (online or onsite) is aimed at intermediate-level data engineers who wish to become proficient in utilizing Azure Synapse Analytics for a wide range of data processing, analytics, and visualization.

By the end of this training, participants will be able to:

• Understand the core concepts, architecture, and components of Azure Synapse Analytics.
• Create, configure, and manage scalable data warehouses using Azure Synapse.
• Master the techniques for ingesting, transforming, and loading data (ETL) from various sources into Azure Synapse.
• Optimize query performance, secure data, and integrate Azure Synapse with Power BI and other tools to visualize data and share insights.

This instructor-led, live training in Medellín (online or onsite) is aimed at intermediate-level data engineers who wish to learn how to use Azure Data Lake Storage Gen2 for effective data analytics solutions.

By the end of this training, participants will be able to:

• Understand the architecture and key features of Azure Data Lake Storage Gen2.
• Optimize data storage and access for cost and performance.
• Integrate Azure Data Lake Storage Gen2 with other Azure services for analytics and data processing.
• Develop solutions using the Azure Data Lake Storage Gen2 API.
• Troubleshoot common issues and optimize storage strategies.

In this instructor-led, live training in Medellín (online or onsite), participants will learn how to set up and manage a production-scale container environment using Kubernetes on AKS. 

By the end of this training, participants will be able to:

• Configure and manage Kubernetes on AKS.
• Deploy, manage and scale a Kubernetes cluster.
• Deploy containerized (Docker) applications on Azure.
• Migrate an existing Kubernetes environment from on-premise to AKS cloud.
• Integrate Kubernetes with third-party continuous integration (CI) software.
• Ensure high availability and disaster recovery in Kubernetes.

This course teaches IT Professionals how to manage their Azure subscriptions, secure identities, administer the infrastructure, configure virtual networking, connect Azure and on-premises sites, manage network traffic, implement storage solutions, create and scale virtual machines, implement web apps and containers, back up and share data, and monitor your solution.

This course is for Azure Administrators. The Azure Administrator implements manages and monitors identity, governance, storage, compute, and virtual networks in a cloud environment. The Azure Administrator will provision, size, monitor, and adjust resources as appropriate.

This instructor-led, live training in Medellín (online or onsite) is aimed at beginner-level / intermediate-level / advanced-level developers and technical professionals who wish to use Microsoft Azure to build, test, and deploy AI agents for business applications.

By the end of this training, participants will be able to: understand AI agent architecture on Azure, create and configure a working agent, connect agents to business knowledge sources, evaluate and prepare agents for deployment.

This instructor-led, live training in Medellín (online or onsite) is aimed at DevOps engineers, developers, and project managers who wish to utilize Azure DevOps to build and deploy optimized enterprise applications faster than traditional development approaches.

By the end of this training, participants will be able to:

• Understand the fundamental DevOps vocabulary and principles.
• Install and configure the necessary Azure DevOps tools for software development.
• Utilize Azure DevOps tools and services to continuously adapt to the market.
• Build enterprise applications and evaluate current development processes upon Azure DevOps solutions.
• Manage teams more efficiently and accelerate software deployment time.
• Adopt DevOps development practices within the organization.

This instructor-led, live training in (online or onsite) is aimed at machine learning engineers who wish to use Azure Machine Learning and Azure DevOps to facilitate MLOps practices.

By the end of this training, participants will be able to:

• Build reproducible workflows and machine learning models.
• Manage the machine learning lifecycle.
• Track and report model version history, assets, and more.
• Deploy production ready machine learning models anywhere.