Cloud Computing Training in Prague

This instructor-led, live training session (online or onsite) is tailored for beginner-level data engineers who wish to utilize Azure Data Factory to implement scalable and efficient data integration solutions in the cloud.

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

• Understand the core concepts and architecture of Azure Data Factory (ADF).
• Learn to create, schedule, and monitor data pipelines.
• Integrate with various data sources, perform data transformation, and manage data flows.
• Implement best practices for error handling and performance optimization.
• Secure and monitor data pipelines for production environments.

This instructor-led, live training in Prague (online or onsite) is aimed at intermediate-level IT professionals who wish to develop the skills required to deploy, manage, and operate workloads on Google Cloud and prepare for the Google Certified Associate Cloud Engineer certification.

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

• Set up and manage Google Cloud projects, resources, networking, and storage services.
• Deploy and administer applications using Compute Engine, Google Kubernetes Engine (GKE), Cloud Run, and App Engine.
• Configure identity and access management, security controls, and billing budgets, alerts, and cost monitoring.
• Provision and automate cloud infrastructure using Terraform and Cloud Build.
• Monitor, troubleshoot, and optimize Google Cloud environments using Cloud Monitoring and Cloud Logging.
• Understand the capabilities of Vertex AI and Google Cloud AI services for common business and operational use cases.

This instructor-led live training, available online or on-site, is designed for intermediate-level data scientists and healthcare professionals seeking to harness AI for advanced healthcare applications using Google Colab.

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

• Deploy AI models for healthcare using Google Colab.
• Apply AI for predictive modeling in healthcare data.
• Analyze medical images with AI-driven techniques.
• Examine ethical considerations in AI-based healthcare solutions.

This instructor-led live training in Prague (online or onsite) targets intermediate-level data scientists and engineers who wish to employ Google Colab and Apache Spark for big data processing and analytics.

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

• Set up a big data environment using Google Colab and Spark.
• Process and analyze large datasets efficiently with Apache Spark.
• Visualize big data in a collaborative environment.
• Integrate Apache Spark with cloud-based tools.

This instructor-led, live training in Prague (online or on-site) is designed for beginner-level system administrators seeking to learn the essential concepts and practical skills required for the effective management and optimization of Nutanix environments.

Upon completion of this training, participants will be able to:

• Grasp the fundamentals of the Nutanix Enterprise Cloud Platform and its core components.
• Install, configure, and administer Nutanix Clusters.
• Develop proficiency in managing the Acropolis Hypervisor (AHV).
• Execute advanced management procedures and troubleshoot issues.
• Apply best practices for ensuring high availability, disaster recovery, and security.

This instructor-led live training in Prague (online or onsite) is designed for intermediate-level data professionals who want to apply time series forecasting techniques to real-world data using Google Colab.

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

• Understand the basics of time series analysis.
• Use Google Colab to work with time series data.
• Apply ARIMA models to forecast data trends.
• Utilize Facebook’s Prophet library for flexible forecasting.
• Visualize time series data and forecasting results.

This instructor-led, live training in Prague (online or onsite) is aimed at beginner-level IT professionals who wish to manage and operate the Google Cloud Platform.

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

• Understand the core services and infrastructure of GCP.
• Learn how to manage networks and virtual machines.
• Understand and apply general security best practices in GCP.
• Explore Kubernetes and container management in GCP.
• Learn about storage options and how to configure them.
• Deploy and configure databases on GCP.

This instructor-led, live training in Prague (online or on-site) is tailored for advanced professionals aiming to deepen their understanding of reinforcement learning and its practical applications in AI development using Google Colab.

Upon completion of this training, participants will be able to:

• Grasp the fundamental concepts behind reinforcement learning algorithms.
• Build reinforcement learning models using TensorFlow and OpenAI Gym.
• Create intelligent agents that learn via trial and error.
• Enhance agent performance through advanced techniques like Q-learning and deep Q-networks (DQNs).
• Train agents within simulated environments provided by OpenAI Gym.
• Deploy reinforcement learning models for real-world use cases.

This instructor-led, live training in Prague (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of computer vision and explore TensorFlow's capabilities for developing sophisticated vision models using Google Colab.

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

• Build and train convolutional neural networks (CNNs) using TensorFlow.
• Leverage Google Colab for scalable and efficient cloud-based model development.
• Implement image preprocessing techniques for computer vision tasks.
• Deploy computer vision models for real-world applications.
• Use transfer learning to enhance the performance of CNN models.
• Visualize and interpret the results of image classification models.

This instructor-led, live training in Prague (online or onsite) targets advanced professionals aiming to deepen their understanding of machine learning models, refine their hyperparameter tuning skills, and master effective model deployment via Google Colab.

Upon completion of this training, participants will be able to:

• Build advanced machine learning models using widely adopted frameworks such as Scikit-learn and TensorFlow.
• Enhance model performance through systematic hyperparameter tuning.
• Deploy machine learning models into real-world applications utilizing Google Colab.
• Collaborate on and manage large-scale machine learning projects within Google Colab.

This instructor-led, live training in Prague (online or on-site) is designed for intermediate-level data scientists and developers who wish to apply NLP techniques using Python in Google Colab.

Upon completion of this training, participants will be able to:

• Comprehend the fundamental concepts of natural language processing.
• Preprocess and clean text data specifically for NLP applications.
• Conduct sentiment analysis utilizing NLTK and SpaCy libraries.
• Manage text data in Google Colab to facilitate scalable and collaborative development workflows.

This instructor-led, live training in Prague (online or onsite) is aimed at intermediate-level data scientists and developers who wish to understand and apply deep learning techniques using the Google Colab environment.

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

• Set up and navigate Google Colab for deep learning projects.
• Understand the fundamentals of neural networks.
• Implement deep learning models using TensorFlow.
• Train and evaluate deep learning models.
• Utilize advanced features of TensorFlow for deep learning.

This instructor-led, live training in Prague (online or onsite) is aimed at intermediate-level data engineers, cloud architects, and business intelligence professionals who wish to master data management in industry-specific cloud environments.

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

• Understand the principles and components of data fabrics.
• Design and implement data integration and orchestration solutions.
• Ensure data quality and governance within industry cloud platforms.
• Utilize data fabrics to support industry-specific data analysis and decision-making.
• Stay current with emerging trends and technologies in cloud data management.

This instructor-led, live training in Prague (online or onsite) is tailored for beginner-level IT professionals, business analysts, and project managers seeking to understand the fundamentals of cloud computing and its applications across various industries.

Upon completing this training, participants will be equipped to:

• Identify the core characteristics and advantages of cloud computing.
• Understand the distinctions between different cloud service and deployment models.
• Appreciate the value of industry-specific cloud solutions.
• Evaluate the security and compliance dimensions of cloud platforms.
• Explore emerging trends and future developments in cloud technology.

This instructor-led, live training in Prague (online or onsite) is aimed at intermediate-level cloud engineers and operations managers who wish to improve their cloud infrastructure management using Kubiya AI.

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

• Integrate Kubiya AI into cloud infrastructure.
• Automate cloud resource provisioning and management.
• Optimize cloud costs using AI-powered analytics.
• Enhance cloud security with AI-driven monitoring.

This instructor-led, live training in Prague (online or onsite) is aimed at intermediate-level data scientists and developers who wish to apply machine learning algorithms efficiently using the Google Colab environment.

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

• Set up and navigate Google Colab for machine learning projects.
• Understand and apply various machine learning algorithms.
• Use libraries like Scikit-learn to analyze and predict data.
• Implement supervised and unsupervised learning models.
• Optimize and evaluate machine learning models effectively.

This instructor-led, live training in Prague (online or onsite) is aimed at beginner-level to advanced-level DevOps engineers, system administrators, and system architects who wish to enhance their Terraform skills and proficiency in managing complex infrastructure deployments.

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

• Develop and maintain Terraform projects at scale.
• Demonstrate expertise with HCL and some of the more-advanced expression language capabilities and practices.
• Utilize various automation tools and processes for managing Terraform ops in continuous integration and delivery pipelines, including testing and quality assurance tools and processes.
• Act as an expert in any existing or new Terraform project or module.

This instructor-led, live training in Prague (online or onsite) is aimed at beginner-level data scientists who wish to learn how to create meaningful and visually appealing data visualizations.

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

• Set up and navigate Google Colab for data visualization.
• Create various types of plots using Matplotlib.
• Utilize Seaborn for advanced visualization techniques.
• Customize plots for better presentation and clarity.
• Interpret and present data effectively using visual tools.

This instructor-led, live training in Prague (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of DevOps practices and streamline development processes using AWS Cloud9.

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

• Set up and configure AWS Cloud9 for DevOps workflows.
• Implement continuous integration and continuous delivery (CI/CD) pipelines.
• Automate testing, monitoring, and deployment processes using AWS Cloud9.
• Integrate AWS services such as Lambda, EC2, and S3 into DevOps workflows.
• Utilize source control systems like GitHub or GitLab within AWS Cloud9.

This instructor-led, live training in Prague (online or on-site) targets beginner-level developers and data analysts interested in learning Python programming from scratch via Google Colab.

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

• Understand the foundational concepts of the Python programming language.
• Implement Python code within the Google Colab environment.
• Employ control structures to direct the flow of a Python program.
• Build functions to organize and reuse code effectively.
• Explore and apply essential libraries for Python programming.

This instructor-led live training in Prague (online or onsite) is designed for intermediate to advanced-level integration developers and system administrators who wish to learn advanced Boomi techniques for building, managing, and deploying cloud-based solutions on integration platforms.

Upon completion of this training, participants will be able to:

• Utilize AtomSphere and effectively manage Boomi documents.
• Design and create complex integration processes featuring advanced logic and data processing capabilities.
• Manage integration process deployments, logging, and reporting.
• Effectively capture and handle errors.
• Apply best practices and techniques for seamless Boomi integration.

This instructor-led, live training session in Prague (online or onsite) is aimed at beginner-level data scientists and IT professionals who wish to learn the basics of data science using Google Colab.

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

• Set up and navigate Google Colab.
• Write and execute basic Python code.
• Import and handle datasets.
• Create visualizations using Python libraries.

This instructor-led, live training in Prague (online or onsite) targets intermediate-level professionals who want to learn how to effectively build, deploy, and maintain serverless applications on AWS Cloud9 and AWS Lambda.

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

• Understand the fundamentals of serverless architecture.
• Set up AWS Cloud9 for serverless application development.
• Develop, test, and deploy serverless applications using AWS Lambda.
• Integrate AWS Lambda with other AWS services such as API Gateway and S3.
• Optimize serverless applications for performance and cost efficiency.

This instructor-led, live training in Prague (online or onsite) is aimed at developers, system administrators, and cloud enthusiasts who wish to gain practical knowledge of OpenNebula and use it for their cloud solutions.

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

• Set up a development environment that includes OpenNebula.
• Create and manage virtual machines in OpenNebula.
• Understand the lifecycle of a virtual machine.
• Integrate OpenNebula with existing infrastructure.
• Troubleshoot common issues in an OpenNebula environment.

This instructor-led live training in Prague (online or onsite) targets intermediate-level system administrators who wish to utilize VMware vCenter to manage complex virtual environments.

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

• Understand the architecture and components of VMware vSphere and vCenter Server.
• Install, configure, and manage VMware ESXi and vCenter Server.
• Implement advanced networking and storage configurations.
• Create, manage, and migrate virtual machines.
• Ensure high availability and disaster recovery in a virtualized environment.
• Automate vSphere tasks and manage lifecycle and upgrades.
• Troubleshoot common issues and apply best practices.

This intensive OpenStack training offers practical, hands-on experience in deploying, managing, troubleshooting, and optimizing private cloud environments built on OpenStack. Designed as an extended bootcamp, the course covers core administration topics, real-world troubleshooting scenarios, and advanced architectural concepts aligned with the Certified OpenStack Administrator exam objectives. With 75% workshop-based learning in a live OpenStack lab, participants build the skills needed to confidently administer and further develop enterprise OpenStack infrastructures.

This instructor-led, live training in Prague (on-site 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.

This instructor-led live training in Prague (available on-site or remotely) is tailored for developers looking to use AWS Lambda for building and deploying cloud services and applications, eliminating the need to manage execution environments like servers, VMs, and containers, as well as their availability, scalability, and storage.

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

• Configure AWS Lambda to execute functions.
• Understand FaaS (Functions as a Service) and the advantages of serverless development.
• Build, upload, and run AWS Lambda functions.
• Integrate Lambda functions with various event sources.
• Package, deploy, monitor, and troubleshoot Lambda-based applications.

This instructor-led, live training in Prague (online or onsite) is tailored for integration developers, system administrators, and system integrators who wish to use Boomi to build, manage, and deploy integration platforms for cloud-based solutions.

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

• Set up the necessary environment to start building integrations with Boomi.
• Understand Boomi AtomSphere's features, architecture, and core concepts.
• Learn how to design, build, and deploy integration processes with Boomi.
• Use Boomi's dashboard and reporting options to monitor applications.
• Manage configurations and deployments for Atom, Molecule, and Atom Cloud.
• Enable web services and API integration and management with Boomi.

This intensive 7-day programme offers a practical, in-depth exploration into the design, deployment, and operation of cloud-native applications using contemporary DevOps methodologies.

Attendees will discover how to architect scalable microservices, refine container environments, and manage production workloads effectively with Kubernetes. The curriculum includes advanced deployment techniques, GitOps-driven automation, and observability strategies to guarantee system reliability and high performance.

Significant emphasis is placed on addressing real-world operational challenges, such as incident response, failure simulation, and root cause analysis. The course finishes by leveraging AI-powered tools to aid in troubleshooting and expedite operational decision-making processes.

Upon completion of this training, participants will possess a solid understanding of how to construct, deploy, monitor, and sustain resilient distributed systems within a Kubernetes-based ecosystem.

Designed specifically for non-technical professionals—including managers, business analysts, QA testers, and operations staff—this course provides a solid foundation in cloud computing. Attendees will delve into the essential concepts, advantages, and real-world applications of cloud technology, enabling them to make better-informed decisions and actively support cloud migration efforts. The focus is on demystifying technical jargon, contrasting cloud solutions with on-premise infrastructure, clarifying service models, and illustrating how cloud technology influences different organizational roles.

Upon completion of this course, participants will be capable of:

• Grasping the primary definitions and terminology associated with cloud computing
• Distinguishing between various cloud service models (IaaS, PaaS, SaaS)
• Differentiating among cloud deployment strategies (Public, Private, Hybrid, Multi-Cloud)
• Comparing on-premises infrastructure with cloud-based solutions
• Understanding key cloud benefits: scalability, agility, availability, and cost-efficiency
• Identifying major cloud platforms (AWS, Azure, GCP) and their respective services
• Comprehending cloud accountability, including the shared responsibility model and role-based access
• Recognizing the influence of cloud computing on software testing, deployment, and monitoring
• Engaging constructively in cloud adoption and migration projects
• Appreciating fundamental cloud security, compliance, and governance principles

This intensive 3-day training program is crafted to equip participants with a robust understanding of cloud computing principles, complemented by practical, hands-on experience across the industry's top cloud platforms: AWS, Microsoft Azure, and Google Cloud Platform (GCP). The curriculum is divided into four focused sessions, each dedicated to a major cloud provider, beginning with an overview of core cloud computing concepts. Upon completion, attendees will possess a comprehensive grasp of cloud fundamentals, detailed insight into the architecture and services of each platform, and the ability to deploy and manage resources in real-world contexts.

This instructor-led, live training in Prague (online or onsite) is designed for IT architects and consultants who aim to apply best practices for cloud infrastructure and services.

Upon completing this training, participants will be able to:

• Utilize cloud infrastructure and services to support business implementation strategies.
• Implement advanced cloud security measures aligned with Cloud Security Alliance standards.
• Transition legacy systems to the cloud by leveraging the synergy between Service-Oriented Architecture (SOA) and Platform as a Service (PaaS).
• Automate the on-demand provisioning of resources for asynchronous cloud services.

This instructor-led live training in Prague (online or onsite) targets cloud administrators, cloud architects, technology leaders, and financial analysts who wish to record, manage, monitor, and process an organization's financial assets in the cloud.

By the end of this training, participants will be able to use FinOps practices within their organizations to forecast costs, optimize processes, and perform financial management operations in the cloud.

This live, instructor-led training in Prague is aimed at beginner-level business professionals who wish to prepare for the Google Cloud Digital Leader certification.

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

• Explain how Google Cloud drives digital and data transformation.
• Describe Google Cloud AI/ML, infrastructure, security, and operations at a business level.
• Prepare for the certification exam with mock questions and structured review.

This instructor-led live training in Prague (online or onsite) is designed for intermediate-level IT professionals and technology decision-makers who intend to use open-source platforms and standards to design portable, resilient, and sovereign software environments.

By the end of this training, participants will be able to explain digital sovereignty concepts, assess portability risks, evaluate Kubernetes and open-source platform options, and define practical adoption steps.

This program serves as comprehensive training for OpenStack. It commences with an introduction to the
system, followed by practical workshops that equip participants with the skills to manage private
clouds built on OpenStack, and concludes with topics on troubleshooting and advanced architectural concepts. The primary objective is to familiarize learners with the OpenStack ecosystem while establishing a solid foundation for further expansion and optimization of OpenStack clouds.
The course covers all necessary topics required to successfully complete the OpenStack
Administrator certification exam.

This instructor-led, live training (available online or onsite) targets system administrators and infrastructure engineers seeking to design, deploy, and manage private OpenStack cloud infrastructure for enterprise environments.

By the end of this training, participants will be able to understand OpenStack architecture, deploy private cloud infrastructure, manage compute and storage resources, implement security with Keystone, and apply enterprise best practices.

This instructor-led, live training in Prague (online or onsite) is aimed at intermediate-level IT leaders, architects, and governance professionals who wish to use sovereign cloud strategy principles to design governance models, choose suitable cloud architectures, and prepare realistic cloud exit plans.

By the end of this training, participants will be able to: define sovereignty requirements, evaluate architecture options, establish governance controls, and build a practical exit roadmap.

This instructor-led, live training in Prague (online or onsite) is designed for intermediate-level virtualization administrators who wish to use open-source platforms to migrate away from VMware.

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

• Install and configure KVM, oVirt, and Proxmox VE.
• Migrate virtual workloads from VMware.
• Implement high availability and disaster recovery.
• Optimize performance in open-source virtualization environments.