
Online or onsite, instructor-led live Cloud Computing training courses demonstrate through hands-on practice the fundamentals of cloud computing and how to benefit from cloud computing.
Cloud Computing 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 Cloud Computing trainings in the UK can be carried out locally on customer premises or in NobleProg corporate training centres.
NobleProg -- Your Local Training Provider
Testimonials
Experience testing a real-world cluster was good and it was interesting to hear about Rena to's real experiences of operating OpenStack.
UKRI - UK Shared Business Services Ltd
Course: OpenStack Administration - Basic + Intermediate (Certified System Administrator for OpenStack)
I mostly enjoyed the interaction with the trainer.
UKRI - UK Shared Business Services Ltd
Course: OpenStack Administration - Basic + Intermediate (Certified System Administrator for OpenStack)
He knew what he was talking about
KnowledgePool
Course: Terraform for Managing Cloud Infrastructure
Reda took onboard suggestions for changes to approaches and as a result being able to walk through the examples with explanations as to what was happening/expected/required etc was very beneficial and helped my understanding, thank you Reda.
KnowledgePool
Course: Terraform for Managing Cloud Infrastructure
The exercises which we did during Friday morning, they were presented at a time when concentration was peak, with plenty of scope for guidance when required.
Roni Colling - KnowledgePool
Course: Terraform for Managing Cloud Infrastructure
very knowledgeable
Tony Edogiawerie - KnowledgePool
Course: Terraform for Managing Cloud Infrastructure
The trainer was knowledgeable in many related technical areas and displayed a real passion for the subject being taught
KnowledgePool
Course: Terraform for Managing Cloud Infrastructure
It was fast paced, but that keeps us on our toes, I requested the material to be sent to me, and it has been, so I am now able to review this at a more measured pace, to fully digest the content
Rupert Hirst - KnowledgePool
Course: Terraform for Managing Cloud Infrastructure
Mix of lectures and practical exercises
KnowledgePool
Course: Terraform for Managing Cloud Infrastructure
lab exercises
Global Knowledge Network Training Limited
Course: Terraform for Managing Cloud Infrastructure
Trainer is trying to answer to the additional requests, even if it involves to change his plans.
ORANGE
Course: Cloud computing essentials for managers / software engineers
Jorge tries his best to help with our environment setups and other things we want to try.
JIMMY CHUN MING CHAN - THALES TRANSPORT & SECURITY (HONG-KONG) LIMITED
Course: Developing for Cloud Foundry
I genuinely liked the new technology.
PCCW
Course: AWS Developer Associate
Practice parts
Instytut Lotnictwa
Course: AWS Developer Associate
The training is practical and it is good for understanding how to use AWS step by step
PCCW
Course: AWS Developer Associate
That the trainer was able to adapt to specific questions/situations
Inforit BV
Course: Kubernetes on Azure (AKS)
That she asked for feedback everyday to improve on the next day's lectures
Bacher Systems EDV GmbH
Course: Terraform Fundamentals for Beginners
That it was all new technology and offerings to myself. After being shown how quick and easy it is to set up certain services in AWS, I feel I could get a real benefit out of it for quick project and proposal prototyping.
MDA Systems Ltd.
Course: AWS Developer Associate
Fernando knew the products and how to use them. His willingness and friendliness to assist in the hands-on lab was great.
MDA Systems Ltd.
Course: AWS Developer Associate
There was a good general pass over what seemed like the most important parts of AWS. The instructor was open to questions and addressed areas of AWS that were not part of the outline based on our questions.
MDA Systems Ltd.
Course: AWS Developer Associate
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
Thought it was a good overview of a lot of different services. Liked the detail on IAS.
MDA Systems Ltd.
Course: AWS Developer Associate
Explaining why it's financially viable to do these things
MDA Systems Ltd.
Course: AWS Developer Associate
It provided context for the things we do in AWS.
MDA Systems Ltd.
Course: AWS Developer Associate
Everything. I had played around with AWS before but just on my own personal time. The training really brought everything together, with real world examples and how many individual pieces can be bolted together for a applicable solution.
Matt Sartain - MDA Systems Ltd.
Course: AWS Developer Associate
Hands-on labs
MDA Systems Ltd.
Course: AWS Developer Associate
To get a better understanding about OpenStack.
Jan Gustafsson - Polystar OSIX
Course: OpenStack Architecture and Troubleshooting
It was very easy communication during all the course, got answers and help in very pedagogical manner. The trainer is very experienced, I recommend him anyone who is interested in getting good knowledge in this very complicated area :-)
Polystar OSIX
Course: OpenStack Architecture and Troubleshooting
The broad perspective of Openstack, no chance to dive in to deep to be able to keep schedule, more to where to get information from.
Jörgen Selegran - Polystar OSIX
Course: OpenStack Architecture and Troubleshooting
A good mix of hands on exercises and lectures!
Polystar OSIX
Course: OpenStack Architecture and Troubleshooting
The flexibility to answer questions. Good pdf, good examples
Conny Vigström - Polystar OSIX
Course: OpenStack Architecture and Troubleshooting
Damian, is very skilled, I'm very pleased with everything, no complains, best training session I've participated in for a long time… It's very difficult to have a training course like this, totally remote, you did a great job, It went very well, there were no issues.
Peter Erlandsson - Polystar OSIX
Course: OpenStack Architecture and Troubleshooting
The virtual desktop in a browser feature was kind of neat.
Mikael Karlsson - Polystar OSIX
Course: OpenStack Architecture and Troubleshooting
The network parts.
Polystar OSIX
Course: OpenStack Architecture and Troubleshooting
The varied topics
Daniel Lindh - Tele 2 Sverige AB
Course: OpenStack for Telecom
I like that we before the training had some meetings to discuss what parts we should focus on, and what is interesting for us at Tele2.
Tele 2 Sverige AB
Course: OpenStack for Telecom
The paste, all the information I got.
Tele 2 Sverige AB
Course: OpenStack for Telecom
Playing around in a non production environment.
Tele 2 Sverige AB
Course: OpenStack for Telecom
Learning about Kubernetes.
Felix Bautista - SGS GULF LIMITED ROHQ
Course: Kubernetes on Azure (AKS)
I would say that the trainor really explain well. I like his strategy on teaching. He ensures that we really learn before proceeding to the next topic.
SGS GULF LIMITED ROHQ
Course: Kubernetes on Azure (AKS)
Cloud Computing Course Outlines
From Vision, Speech to Language to Conversational bots, Azure is empowering organizations to process their data to derive insights
This instructor-led, live training (online or onsite) is aimed at AI enthusiasts who wish to use Azure to build AI scenarios in the cloud
By the end of this training, participants will be able to:
- Build Azure based AI scenarios.
- Understand the end to end functioning of API based infering
- Build conversational bots for business needs
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request more details or customized training for this course, please contact us to arrange.
By the end of this training, participants will be able to:
- Install and configure Kubernetes, Kubeflow and other needed software on Azure.
- Use Azure Kubernetes Service (AKS) to simplify the work of initializing a Kubernetes cluster on Azure.
- 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.
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.
By the end of this training, participants will be able to:
- Install and configure Pulumi.
- Declare cloud infrastructure using programming languages.
- Use Pulumi to deploy software using VMs, networks, and databases, as well as Kubernetes clusters and serverless functions.
- Deploy software to public, private, and hybrid cloud service infrastructures.
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.
This instructor-led, live training (online or onsite) is aimed at technical persons who wish to gain a practical understanding of available cloud solutions, the data analysis processes needed to work with data in the cloud, and the hands-on practice to apply tools such as Power BI to analyze data.
By the end of this training, participants will be able to:
- Install and configure Power BI.
- Evaluate the various data solutions offered by cloud providers such as Azure.
- Gain an understanding of the different structures, modeling approaches, and data warehouse designs used to store, manage and access Big Data.
- Apply tools and techniques to clean data in preparation for analysis.
- Build reporting and analytics solutions based on on-premise as well as cloud data.
- Integrate data analytics solutions with a data warehouse.
- Mitigate data security risks and ensure data privacy.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
By the end of this training, participants will be able to:
- Build machine learning models with zero programming experience.
- Create predictive algorithms with Azure Machine Learning.
- Deploy production ready machine learning algorithms.
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.
By the end of this training, participants will be able to:
- Administrate host security, network security, and more.
- Set up storage and database security in Azure.
- Implement security monitoring using Azure resources.
- Prevent malicious cyber attacks on data and infrastructures.
By the end of this training, participants will be able to:
- Apply Google security practices with 2SV and SSO.
- Monitor domain and services usage through reports in the Admin Console.
- Set up and configure a G Suite Admin Console.
By the end of this training, participants will be able to:
- Provide an alternative to Unix Commands with the MinIO Client.
- Use MinIO to build high performance infrastructures for machine learning, analytics, and more.
- Deploy MinIO on Kubernetes for orchestrated deployment to scale.
- 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.
By the end of this training, participants will be able to:
- Understand and use parallel programming with Fortran in OpenMP.
- Calculate fractals in parallel to render multiple pixels and characters.
- Implement vector programming with SIMD extensions for HPC systems.
- Add parallel blocks for specifying shared memory parallelism.
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.
- Move data in AWS with AWS services.
- Implement operations with AWS DAX.
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.
- Write AWS CloudFormation Templates using YAML.
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.
By the end of this training, participants will be able to:
- Install and configure Terraform.
- Understand the principles of infrastructure as code.
- Set up and automate infrastructure using Terraform.
- Write and share configuration file with team members.
By the end of this training, participants will be able to:
- Write highly-accurate machine learning models using Python, R, or zero-code tools.
- Leverage Azure's available data sets and algorithms to train and track machine learning and deep-learning models.
- Use Azures interactive workspace to collaboratively develop ML models.
- Choose from different Azure-supported ML frameworks such as PyTorch, TensorFlow, and scikit-learn.
By the end of this training, participants will be able to:
- Install and configure Terraform on GCP.
- Implement an "infrastructure as code" approach to managing private and public 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 requirements.
- Collaborate with other infrastructure engineers by sharing configuration files in a common code repository.
- Improve transparency in the infrastructure procurement process.
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.
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.
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.
By the end of this training, participants will be able to use FinOps practices in an organization to forecast costs, optimize processes, and perform financial management operations in the cloud.
By the end of this training, participants will be able to:
- Set up Fn to create directories and functions.
- Create applications using different programming languages.
- Monitor functions to resolve issues at the development and deployment stages.
By the end of this training, participants will be able to strategize, monitor, and manage enterprise-grade productions with serverless models and platforms.