Secure & Portable AI Inference with Docker: From Local to Cloud Training Course

This instructor-led, live training in Slovakia (online or onsite) is aimed at engineers who wish to advance their knowledge of Docker so as to deploy applications at a larger scale while maintaining control.

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

• Create their own Docker images.
• Deploy and manage a large number of Docker applications.
• Evaluate different container orchestration solutions and choose the most suitable one.
• Set up a continuous integration process for Docker applications.
• Integrate Docker applications with existing continuous tools integration processes.
• Secure their Docker applications.

Docker serves as a containerization platform that facilitates the creation of consistent, portable, and reproducible environments specifically designed for AI and machine learning workloads.

This live, instructor-led training, available either online or on-site, is designed for intermediate-level professionals seeking to encapsulate ML codebases, dependencies, and models within Docker to ensure reliable workflows from development through to production.

Upon completion of this course, participants will be equipped to:

• Develop and administer Docker images specifically tailored for AI and ML applications.
• Encapsulate machine learning pipelines, associated tools, and their dependencies.
• Enhance Docker environments to maximize performance and portability.
• Implement containerized ML services across diverse runtime environments.

Course Structure

• Demonstration of key concepts accompanied by facilitated discussions.
• Practical exercises centered on real-world containerization scenarios.
• Application of knowledge through live-lab Docker environments.

Customization Possibilities

• To adapt this training to your specific organizational needs, please reach out to us to discuss the arrangements.

CI/CD for AI represents a systematic methodology for automating the packaging, testing, containerization, and deployment of models through continuous integration and delivery pipelines.

This instructor-led live training (available online or on-site) is designed for intermediate-level professionals seeking to streamline end-to-end AI model delivery workflows using Docker and CI/CD platforms.

Upon completion of the training, participants will be equipped to:

• Establish automated pipelines for building and validating AI model containers.
• Enforce version control and reproducibility throughout the model lifecycle.
• Incorporate automated deployment strategies for AI services.
• Apply CI/CD best practices specifically adapted for machine learning operations.

Format of the Course

• Instructor-guided presentations and technical discussions.
• Practical labs and hands-on implementation exercises.
• Realistic CI/CD workflow simulations in a controlled environment.

Course Customization Options

• If your organization requires customized pipeline workflows or platform integrations, please contact us to tailor this course.

The Certified Kubernetes Administrator (CKA) certification program was established by The Linux Foundation in partnership with the Cloud Native Computing Foundation (CNCF).

Kubernetes has become the dominant platform for container orchestration.

Since 2015, NobleProg has been providing Docker and Kubernetes training. With over 360 successfully completed training projects, we have established ourselves as one of the leading training providers globally in the field of containerization.

Since 2019, we have also assisted our clients in validating their expertise in Kubernetes environments by preparing them to successfully pass the CKA and CKAD exams.

This instructor-led, live training (available online or onsite) is designed for System Administrators and Kubernetes users who wish to validate their knowledge by passing the CKA exam.

Additionally, the training focuses on gaining practical experience in Kubernetes Administration. Therefore, we recommend attending, even if you do not plan to take the CKA exam.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request customized training for this course, please contact us to arrange.
• For more information about CKA certification, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka

The Certified Kubernetes Application Developer (CKAD) certification program was established by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), the organization responsible for hosting Kubernetes.

This instructor-led, live training (available online or on-site) is designed for Developers who want to validate their skills in designing, building, configuring, and exposing cloud-native applications for Kubernetes.

Additionally, the training emphasizes gaining practical experience in Kubernetes application development; therefore, we recommend participating even if you do not plan to take the CKAD exam.

NobleProg has been delivering Docker & Kubernetes training since 2015. With over 360 successfully completed training projects, we have become one of the most well-known training providers globally in the field of containerization. Since 2019, we have also assisted our customers in verifying their performance in k8s environments by preparing and encouraging them to pass the CKA and CKAD exams.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request customized training for this course, please contact us to arrange it.
• To learn more about CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/

Docker is an open-source platform designed to automate the creation, distribution, and execution of applications within containers.

This instructor-led training session (available online or in-person) targets engineers who want to leverage Docker to deploy and manage software as containers rather than relying on traditional standalone installations.

Upon completion of this course, participants will be equipped to:

• Install and configure Docker.
• Comprehend and apply software containerization principles.
• Manage applications based on Docker.
• Establish networks between various Docker applications and systems.
• Understand and modify Docker registries.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical practice.
• Hands-on implementation within a live lab environment.

Customization Options

• To request tailored training for this course, please contact us to make arrangements.
• For further information about Docker, visit: https://www.docker.com

Learn to build, deploy, and administer containerized environments using Docker, Kubernetes, and OpenShift. This five-day, hands-on training covers container images, Kubernetes workloads, cluster networking, storage, security, monitoring, and practical OpenShift administration. Participants acquire the skills necessary to operate modern container platforms and troubleshoot applications across development and production environments.

In this instructor-led, live training in Slovakia (onsite or remote), participants will learn how to create and manage Docker containers, then deploy a sample application inside a container. Participants will also learn how to automate, scale, and manage their containerized applications within a Kubernetes cluster. Finally, the training goes on to more advanced topics, walking participants through the process of securing, scaling and monitoring a Kubernetes cluster.

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

• Set up and run a Docker container.
• Deploy a containerized server and web application.
• Build and manage Docker images.
• Set up a Docker and Kubernetes cluster.
• Use Kubernetes to deploy and manage a clustered web application.
• Secure, scale and monitor a Kubernetes cluster.

Docker serves as a containerization platform that enables the creation of reproducible, portable, and scalable environments for machine learning systems.

Delivered by an instructor in either an online or on-site setting, this live training is tailored for intermediate to advanced technical professionals seeking to operationalize and containerize complete ML pipelines using Docker.

By the end of this program, participants will be equipped to:

• Encapsulate ML training, validation, and inference workloads within containers.
• Architect and manage end-to-end ML pipelines leveraging Docker and auxiliary tools.
• Establish versioning, ensure reproducibility, and implement CI/CD practices for ML components.
• Deploy, observe, and scale ML services within containerized infrastructures.

Course Structure

• Engaging lectures complemented by practical demonstrations.
• Hands-on activities centered on constructing real-world ML pipeline elements.
• Live lab sessions dedicated to implementing end-to-end containerized workflows.

Customization Possibilities

• To tailor the training to specific ML infrastructure requirements, please reach out to discuss available options.

Training objectives: Gain theoretical and practical skills in Docker and Kubernetes.

The "Advanced Docker and Kubernetes" course is a comprehensive training program covering the Kubernetes platform and its ecosystem. It is designed for participants with varying levels of experience, providing a full range of basic and advanced Kubernetes functionalities. Key concepts covered include Containers, Labels, Controllers, Services, Secrets, Persistent Data Volumes, Namespaces, Quotas, the Container Networking Model, Service Discovery, Scaling, Load Balancing, Cluster Management, Kubernetes Installation, Cluster Security, Access Control, Controller High Availability, Monitoring and Logging, Application Auto-Scaling, Advanced Scheduling, Microservices-based Applications, Application Design Patterns, and Deploying Applications on a Kubernetes Cluster.

To execute high-performance deep learning tasks efficiently and at scale, GPU acceleration is a critical requirement.

This live, instructor-led session, available both online and on-site, is designed for intermediate-level technical specialists looking to deploy, fine-tune, and manage GPU-powered AI workloads within Docker environments.

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

• Construct and execute GPU-capable containers for both training and inference phases.
• Set up CUDA, drivers, and runtime libraries to support containerized AI pipelines.
• Refine resource allocation and isolation strategies for GPU-intensive applications.
• Implement scalable, container-based deep learning services in live production settings.

Course Delivery Method

• Engaging instruction reinforced by practical, real-world examples.
• Practice exercises centered on GPU-enabled development workflows.
• Practical implementation within a live laboratory environment.

Customization Possibilities

• To align training with your specific infrastructure or GPU configuration, please reach out to us to discuss tailored options.

Hybrid AI deployment involves executing AI inference across cloud infrastructure, on-premises data centers, and edge environments through unified containerized workflows.

This instructor-led live training, available online or onsite, is designed for advanced professionals aiming to architect and implement distributed AI inference systems within heterogeneous environments.

After completing this training, participants will be able to:

• Create secure and scalable containerized AI services tailored for multi-location setups.
• Deploy AI inference workloads to cloud platforms, local servers, and edge devices using Docker.
• Leverage orchestration tools to automate distributed AI operations.
• Enhance inference latency, reliability, and resilience across diverse infrastructure.

Course Format

• Guided presentations and expert-led discussions.
• Extensive hands-on practice and applied exercises.
• Real-world experimentation in a controlled live-lab environment.

Customization Options

• To tailor this course to your organization’s specific infrastructure or use cases, please contact us for customization.

In this instructor-led, live training in Slovakia (onsite or remote), participants will learn how to deploy a collection of sample servers inside containers, then automate, scale, and manage their containerized servers within a Kubernetes cluster. The training goes on to more advanced topics, walking participants through the process of securing, networking and monitoring a Kubernetes cluster.

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

• Set up and run a Docker container.
• Deploy containerized databases and servers.
• Set up a Docker and Kubernetes cluster.
• Use Kubernetes to deploy and manage different environments under the same cluster.
• Secure, scale and monitor a Kubernetes cluster.

In this instructor-led live training located in Slovakia, participants will learn the fundamentals of building microservices using Spring Cloud and Docker. Participant knowledge is put to the test through exercises and the step-by-step development of sample microservices.

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

• Understand the fundamentals of microservices.
• Use Docker to build containers for microservice applications.
• Build and deploy containerized microservices using Spring Cloud and Docker.
• Integrate microservices with discovery services and the Spring Cloud API Gateway.
• Use Docker Compose for end-to-end integration testing.