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

This instructor-led, live training in Serbia (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:

• Build 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.

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

• Create custom Docker images.
• Deploy and manage a high volume of Docker applications.
• Assess various container orchestration solutions and select the most appropriate option.
• Establish a continuous integration pipeline for Docker applications.
• Integrate Docker applications with existing continuous integration workflows.
• Enhance the security of Docker applications.
• Leverage Kubernetes to deploy and manage multiple environments within a single cluster.
• Secure, scale, and monitor Kubernetes clusters.

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

This instructor-led live training, available online or onsite, targets intermediate-level professionals looking to effectively package ML codebases, dependencies, and models using Docker to ensure reliable workflows from development to production.

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

• Create and maintain Docker images optimized for AI and ML applications.
• Encapsulate machine learning pipelines, tools, and dependencies within containers.
• Tune Docker environments to maximize performance and portability.
• Deploy containerized ML services across various runtime environments.

Course Format

• Concept demonstrations accompanied by guided discussions.
• Hands-on exercises centered on practical containerization tasks.
• Practical implementation utilizing live-lab Docker environments.

Customization Options

• To tailor this training to your specific organizational environment, please reach out to us for 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 onsite) targets intermediate-level professionals aiming to streamline end-to-end AI model delivery workflows using Docker alongside CI/CD platforms.

Upon completing the training, participants will be equipped to:

• Establish automated pipelines for constructing and evaluating AI model containers.
• Enforce version control and reproducibility throughout model lifecycles.
• 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 conducted in a controlled environment.

Course Customization Options

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

The Certified Kubernetes Administrator (CKA) program was established by The Linux Foundation and the Cloud Native Computing Foundation (CNCF).

Today, Kubernetes stands as a leading platform for container orchestration.

NobleProg has been providing Docker and Kubernetes training since 2015. With over 360 successfully completed training projects, we have become one of the most recognized training providers globally in the field of containerization.

Since 2019, we have also been helping our customers validate their performance in Kubernetes environments by preparing them and encouraging them to 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, so we recommend participation even if you do not intend to take the CKA exam.

Course Format

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

Course Customization Options

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

The Certified Kubernetes Application Developer (CKAD) program has been developed by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), the host of Kubernetes.

This instructor-led, live training (online or onsite) is aimed at Developers who wish to confirm their skills in design, build, configure, and expose cloud native applications for Kubernetes.

On the other hand, training is also focused on gaining practical experience in Kubernetes application development, so we recommend taking part in it, even if you don't intend to take CKAD exam.

NobleProg have been delivering Docker & Kubernetes training from 2015. With more than 360 successfully completed training projects, we became one of the best known training company worldwide in field of containerization. Since 2019 we are also helping our customers to confirm their performance in k8s environment by preparing them and encouraging to pass CKA and CKAD exams.

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 a customized training for this course, please contact us to arrange.
• 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 process of building, shipping, and running applications within containers.

This instructor-led live training (available online or onsite) targets engineers who want to use Docker to deploy and manage software as containers rather than traditional stand-alone applications.

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

• Install and configure Docker.
• Grasp and implement software containerization principles.
• Manage Docker-based applications.
• Network various Docker applications and systems.
• Understand and edit Docker registries.

Course Format

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

Customization Options

• To request customized training for this course, please contact us to arrange.
• For more information on Docker, visit: https://www.docker.com

Acquire the skills to build, deploy, and administer containerized environments using Docker, Kubernetes, and OpenShift. This five-day, intensive hands-on training encompasses container images, Kubernetes workloads, cluster networking, storage solutions, security protocols, monitoring techniques, and practical OpenShift administration. Participants will emerge with the competencies required to operate modern container platforms and troubleshoot applications across both development and production environments.

In this instructor-led live training conducted in Serbia (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 designed to create reproducible, portable, and scalable environments for ML systems.

This instructor-led live training, available either online or onsite, targets intermediate to advanced technical professionals looking to containerize and operationalize complete ML pipelines with Docker.

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

• Containerize workloads for ML training, validation, and inference.
• Design and orchestrate comprehensive ML pipelines utilizing Docker and complementary tools.
• Apply versioning, reproducibility, and CI/CD practices to ML components.
• Deploy, monitor, and scale ML services within containerized environments.

Course Format

• Interactive lectures accompanied by practical demonstrations.
• Hands-on exercises centered on developing authentic ML pipeline components.
• Live lab sessions for executing end-to-end containerized workflows.

Customization Options

• To tailor the training to specific ML infrastructure requirements, please contact us to explore available options.

Course Objectives: Gain theoretical and operational skills in Docker and Kubernetes.

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

To achieve high-performance deep learning at scale, GPU acceleration is a critical requirement for both efficiency and throughput.

This instructor-led live training, available either online or onsite, is designed for mid-level technical specialists seeking to master the configuration, optimization, and execution of GPU-enabled AI workloads within Docker environments.

Upon completion, participants will be equipped to:

• Construct and execute GPU-enabled containers for both model training and inference tasks.
• Set up CUDA, drivers, and runtime libraries specifically for containerized AI pipelines.
• Refine resource allocation and isolation strategies for applications with high GPU demands.
• Launch scalable, container-based deep learning services in production settings.

Course Delivery Format

• Engaging instruction backed by practical, real-world examples.
• Task-based exercises centered on GPU-driven development.
• Practical application within a live laboratory setting.

Customization Possibilities

• Seeking training tailored to your specific infrastructure or GPU stack? Please reach out to us to discuss custom arrangements.

Hybrid AI deployment involves executing AI inference across cloud, on-premises, and edge environments through unified, container-based workflows.

This instructor-led live training, available online or on-site, is designed for advanced professionals seeking to architect and implement distributed AI inference systems across diverse environments.

Upon completing this course, participants will be able to:

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

Course Format

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

Customization Options

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

In this instructor-led, live training in Serbia (onsite or remote), participants will learn how to deploy sample servers inside containers, then automate, scale, and manage these containerized servers within a Kubernetes cluster. The training progresses 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.
• Establish a Docker and Kubernetes cluster.
• Utilize Kubernetes to deploy and manage various environments within the same cluster.
• Secure, scale, and monitor a Kubernetes cluster.