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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.
Executing a digital transformation or having trouble filling your tech talent pipeline?
Upskilling & Reskilling
For Tech Teams
Need to stay ahead of technology shifts and upskill your current workforce on the latest technologies?
New Hire Development
for Talent Acquisition
Is your engineering new hire experience encouraging retention or attrition?
For Tech Learning
Looking for in-the-trenches experiences to level-up your internal learning and development offerings?
Chat with one of our tech experts to create a custom on-site or online training program.
If you are not completely satisfied with your training class, we'll give you your money back.
Learn to develop applications in AWS Serverless.
Learn how to work with, configure, and deploy applications to AWS.
Learn AWS and prepare for the AWS Certified Developer Exam
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.
Learn the concepts for establishing security standards in AWS.
Learn a deep dive of AWS Lambda.
Learn the DevOps practice on AWS and a holistic view on DevOps implementation on the cloud platform using tools like Jenkins, Ansible, and Terraform.
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.
Learn how to write, execute, and perform functional and automating testing using AWS as a cloud.
Learn to build end-to-end data applications using Microsoft Azure and understand which tools are best suited to certain problems and use-cases.
Learn how to deploy, configure and manage Azure using Chef.
Learn how to configure, maintain and monitor Azure Virtual Machines and Virtual Networks.
Learn how to build, deploy, and maintain applications in Azure Cloud.
Learn the philosophy, models, goals, practices and tools being used to move to a DevSecOps culture.
Learn how to pass the "Implementing Microsoft Azure Infrastructure Solutions" certification exam.
Learn how to implement AI and ML techniques on Azure.
Learn how to build, deploy, secure, scale, monitor and maintain applications in Azure Cloud.
Learn how to plan and manage cloud team resources more effectively.
Learn how to deploy and manage Azure in private data centers.
Learn the information necessary to pass the Developing Microsoft Azure Solutions Certification Exam.
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).
Learn how to configure and deploy Chef for server infrastructure.
Learn how to write cookbooks for Chef.
Learn the knowledge and practical skills to design and deliver applications in a Cloud Native approach and create more secure, changeable, scalable and available applications.
Learn how to build a Chatbot on Google Cloud and deploy it standalone as well as on Facebook Messenger.
Learn how to perform insightful and responsive data analysis at scale and delight the consumers of the analysis with effective data visualizations.
Learn to build systems on Google Cloud to store and process batch or streaming data.
Learn how to 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 (IT) infrastructure, operations, Big Data, and Machine Learning.
Learn how to analyze large scale, distributed, and real-time datasets with MapReduce and Apache Beam based capabilities of Google Cloud and practice identification and analysis of effective data features for predictive analytics with BigQuery ML and TensorFlow.
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.
Learn how to 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.
Learn how to utilize advanced processes and practices for the platform to improve function and security.
Learn to use Google's BigQuery to explore and gain insights from large datasets.
Learn about the different cloud providers and what they offer.
Learn how to use Java to set up a project with the Google App Engine and integrate it with other Google Cloud services.
Learn how to develop a platform-based infrastructure using Google Cloud.
Learn the fundamental skills needed to manage large scale infrastructure with SaltStack on major cloud providers (AWS, Google Cloud and Azure).
Learn how to create and configure Kubernetes clusters.
Learn the skills required to build, store, and deploy containers using Docker and Kubernetes.
Learn a deeper dive into Kubernetes architecture, concepts, and container management.
Learn about the key operations and configurations utilized when using Kubernetes to automate, deploy, and manage containerized applications.
Learn 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.
Learn how to define and deploy an OpenStack Cloud Architecture.
Learn about an OpenStack Cloud Architecture with hands-on interaction.