Cloud Computing Training
DevelopIntelligence specializes in delivering highly-customized, dedicated, role-based Cloud Computing Training courses to technical teams and organizations.
Instructor-led Cloud Computing Courses
Customized, role-based, expert-led Cloud Computing Training
Before the advent of cloud computing, companies installed and managed their own physical servers and other IT resources. Public cloud computing platforms such as AWS (Amazon Web Services), Azure, and Google Cloud enable companies to rent computing resources such as servers, database storage, and big data processing. This allows them to outsource their IT infrastructure and instead focus on their core products/services.
When not training for us, our cloud computing instructors regularly author technical papers on the evolution of the tools and languages in the field, speak at industry conferences, and contribute to open source projects.
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Training Journal sat down with our CEO for his thoughts on what’s working, and what’s not working.
Learn how to implement Ansible into your DevOps stack.
The Ansible Fundamentals course provides students with basic understanding of Ansible as well as hands-on experience to enable its use in managing configuration environments.
Learn how to work with, configure, and deploy applications to AWS.
AWS for Developers Fast Track -
Learn AWS and prepare for the AWS Certified Developer Exam
AWS for System Administrators -
Learn the key AWS product lines, system administration processes, dev ops processes, H/A strategies, best-practices, and costing models associated with running solutions on the AWS infrastructure.
Teach traditional architects and developers to develop applications in AWS Serverless.
Deep Dive into Amazon Web Services Serverless Lambda -
The program is focused on providing deep dive on amazon web services lambda.
Introduction to AWS for Developers Learning Spike -
Learn how to use AWS as a proficient user of the technology tools.
Learn how to enable the communication and understanding required to effectively support, manage and migrate to AWS.
Testing REST Services in AWS -
Learn how to write, execute, and perform functional and automating testing using AWS as a cloud.
Learn how to deploy, configure and manage Azure using Chef.
Azure for System Administrators -
Learn how to configure, maintain and monitor Azure Virtual Machines and Virtual Networks.
Learn how to build, deploy, and maintain applications in Azure Cloud.
Describe the philosophy, models, goals, practices and tools being used to move to a DevSecOps culture.
Implementing Microsoft Azure Infrastructure Solutions Certification -
Learn how to pass the "Implementing Microsoft Azure Infrastructure Solutions" certification exam.
Introduction to AI and Machine Learning in Azure -
Learn to implement AI and ML techniques on Azure.
Introduction to Azure for Developers -
Learn how to build, deploy, secure, scale, monitor and maintain applications in Azure Cloud.
Introduction to Azure for Managers -
Learn how to plan and manage cloud team resources more effectively.
Introduction to the Azure Stack and VM Managers -
Learn how to deploy and manage Azure in private data centers.
Microsoft Azure Certification Fast Track -
Learn about the information necessary to pass the Developing Microsoft Azure Solutions Certification Exam
Working with Big Data on Azure -
Learn how to use Big Data technologies on the Azure cloud.
Learn how to use Chef to automate the configuration, deployment, management and test of server infrastructure.
Learn how to use Chef-specific tools and tactics such as Ohai plugins, Chef handlers, ChefSpec, and Custom Light-Weight Resource Providers (LWRP's).
Introduction to Chef Learning Spike -
Learn how to configure and deploy Chef for server infrastructure.
Learn how to write cookbooks for Chef.
Learn how to work with, configure, and deploy applications to AWS.
AWS for Developers Fast Track -
Learn AWS and prepare for the AWS Certified Developer Exam
Provide students with the knowledge required to build, store, and deploy containers using Docker and Kubernetes.
Describe the philosophy, models, goals, practices and tools being used to move to a DevSecOps culture.
Google Cloud for Data Analysts -
Learn how to perform insightful and responsive data analysis at scale and delight the consumers of the analysis with effective data visualizations.
Google Cloud for Data Engineers -
Learn to build systems on Google Cloud to store and process batch or streaming data.
Google Cloud for Data Scientists -
Create and deploy high-performance data science and machine learning systems on Google Cloud for regression and classification use cases leveraging both structured and unstructured datasets.
Learn to create and deploy software on Google Cloud to have secure and stable applications.
Intermediate Google Cloud For Data Analysts -
Learn how to analyze large scale, distributed, and real-time datasets with MapReduce and Apache Beam based capabilities of Google Cloud.
Intermediate Google Cloud for Data Engineers -
Learn how to use data engineering on Google Cloud to build specialized data pipelines for large scale streaming data analytics, machine learning, and recommendation systems.
Intermediate Google Cloud For Data Scientists -
Implement statistical and machine learning models using TensorFlow, for example for recommendation engines, and how to improve their performance based on the students’ understanding of underlying mathematical principles.
Intermediate Google Cloud for Developers -
Utilize advanced processes and practices for the platform to improve function and security.
Introduction to AI and Machine Learning in Azure -
Learn to implement AI and ML techniques on Azure.
Introduction to SageMaker for Data Analysts -
Teach developers how to choose the right questions to ask and how to answer them with Machine Learning.
Learn how to enable the communication and understanding required to effectively support, manage and migrate to AWS.
Ensure a comprehensive understanding of Spinnakers features and capabilities in relation to the standard continuous delivery and deployment concepts it supports.
Provide students with the knowledge required to build, store, and deploy containers using Docker and Kubernetes.
Learn how to utilize Docker for distributed apps.
Introduction to Docker Learning Spike -
Learn the basics about systems and application design using Docker.
Google Cloud for Data Analysts -
Learn how to perform insightful and responsive data analysis at scale and delight the consumers of the analysis with effective data visualizations.
Google Cloud for Data Engineers -
Learn to build systems on Google Cloud to store and process batch or streaming data.
Google Cloud for Data Scientists -
Create and deploy high-performance data science and machine learning systems on Google Cloud for regression and classification use cases leveraging both structured and unstructured datasets.
Learn to create and deploy software on Google Cloud to have secure and stable applications.
Learn a technical overview of Google Cloud and its capabilities in the areas of information technology infrastructure, operations, big data, and machine learning.
Intermediate Google Cloud For Data Analysts -
Learn how to analyze large scale, distributed, and real-time datasets with MapReduce and Apache Beam based capabilities of Google Cloud.
Intermediate Google Cloud for Data Engineers -
Learn how to use data engineering on Google Cloud to build specialized data pipelines for large scale streaming data analytics, machine learning, and recommendation systems.
Intermediate Google Cloud For Data Scientists -
Implement statistical and machine learning models using TensorFlow, for example for recommendation engines, and how to improve their performance based on the students’ understanding of underlying mathematical principles.
Intermediate Google Cloud for Developers -
Utilize advanced processes and practices for the platform to improve function and security.
Empower developers to use Google's BigQuery to explore and gain insights from large datasets.
Introduction to Cloud Computing -
This course provides an overview of the different cloud providers and what they offer.
Introduction to the Google App Engine -
Learn how to use Java to set up a project with the Google App Engine and integrate it with other Google Cloud services.
Moving to a Hybrid Cloud for Managers Adding Google Cloud -
This course explores the development of a platform-based infrastructure using Google Cloud.
Learn how to create and configure Kubernetes clusters.
Provide students with the knowledge required to build, store, and deploy containers using Docker and Kubernetes.
This course covers the key operations and configurations utilized when using Kubernetes to automate, deploy, and manage containerized applications.
To gain a comprehensive understanding of Helm and how to use it to package and manage Kubernetes workloads.
Learn how to build an open cloud with OpenStack.
OpenStack Cloud Architecture and Deployment -
Learn how to define and deploy an OpenStack Cloud Architecture.
OpenStack Cloud Architecture and Deployment Hack-a-thon -
Learn about an OpenStack Cloud Architecture with hands-on interaction.
Learn how to automate an Information Technology (IT) infrastructure utilizing Puppet.
Express infrastructure across multiple teams within an enterprise using Terraform.
