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

This instructor-led, live training in Kenya (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 manager 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 consistent, portable, and reproducible environments for AI and machine learning workloads.

This instructor-led, live training (available online or onsite) is designed for intermediate-level professionals seeking to package ML codebases, dependencies, and models using Docker to ensure reliable development-to-production workflows.

Upon completing this course, participants will be equipped to:

• Construct and manage Docker images customized for AI and ML applications.
• Containerize machine learning pipelines, tools, and dependencies.
• Optimize Docker environments to enhance performance and portability.
• Deploy containerized ML services across various runtime environments.

Course Format

• Conceptual demonstrations accompanied by guided discussions.
• Hands-on exercises targeting real-world containerization tasks.
• Practical implementation within live-lab Docker environments.

Course Customization Options

• To tailor this training to your organizational needs, please reach out to us to coordinate.

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

This instructor-led training, available both online or onsite, targets intermediate-level professionals looking to automate end-to-end AI model delivery workflows using Docker and CI/CD platforms.

Upon completing the training, participants will be able to:

• Establish automated pipelines for building and testing AI model containers.
• Enforce version control and reproducibility across model lifecycles.
• Incorporate automated deployment strategies for AI services.
• Apply CI/CD best practices specifically tailored to machine learning operations.

Course Format

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

Course Customization Options

• Should your organisation require customised pipeline workflows or platform integrations, please reach out to us to tailor this course accordingly.

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

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

NobleProg has been delivering 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 assisting our customers in validating their performance in Kubernetes environments by preparing them and encouraging them to take 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 emphasizes gaining practical experience in Kubernetes Administration; therefore, we recommend participating even if you do not plan to take the CKA exam.

Course Format

• Interactive lectures and discussions.
• Ample 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.
• For more information about CKA certification, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka

The Certified Kubernetes Application Developer (CKAD) programme was developed by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), the host organisation of Kubernetes.

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

Furthermore, the training emphasises gaining practical experience in Kubernetes application development. Therefore, we recommend participating even if you do not intend to sit for 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 recognised training companies globally in the field of containerisation. Since 2019, we have also assisted our customers in validating their performance in k8s environments by preparing them and encouraging them to pass the CKA and CKAD exams.

Format of the Course

• 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 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 deploy and manage software as containers rather than as traditional standalone programs.

Upon completing this training, participants will be able to:

• Install and configure Docker.
• Comprehend and implement software containerization.
• Manage applications based on Docker.
• Connect various Docker applications and systems via networking.
• Understand and modify Docker registries.

Format of the Course

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

Course Customization Options

• To request customized training for this course, please get in touch with us to arrange it.
• To learn more about Docker, please visit: https://www.docker.com

Learn how 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 gain the skills needed to operate modern container platforms and troubleshoot applications across development and production environments.

In this instructor-led live training in Kenya (onsite or remote), participants will learn how to create and manage Docker containers before deploying a sample application inside one. Attendees will also discover how to automate, scale, and manage their containerized applications within a Kubernetes cluster. The training progresses to more advanced topics, guiding participants through the processes 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 powerful containerization platform, enabling the creation of reproducible, portable, and scalable environments tailored for machine learning systems.

This instructor-led, live training, available either online or onsite, is designed for intermediate to advanced technical professionals seeking to containerize and operationalize comprehensive ML pipelines using Docker.

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

• Containerize ML training, validation, and inference workloads effectively.
• Design and orchestrate end-to-end ML pipelines leveraging Docker and complementary tools.
• Implement robust versioning, reproducibility, and CI/CD practices for ML components.
• Deploy, monitor, and scale ML services within containerized environments.

Course Format

• Interactive lectures enhanced by practical demonstrations.
• Hands-on exercises centered on constructing real-world ML pipeline components.
• Live-lab sessions implementing end-to-end containerized workflows.

Course Customization Options

• For training tailored to specific ML infrastructure requirements, please reach out to discuss available options.

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

The 'Advanced Docker and Kubernetes' course is a comprehensive training covering the Kubernetes platform and its ecosystem. It is addressed to participants with varied backgrounds, ensuring a complete scope of both basic and advanced Kubernetes features. It includes key concepts such as Pods, Labels, Controllers, Services, Secrets, Persistent Data Volumes, Claims, Namespaces, Quotas, Container Networking Model, Service Discovery, Scaling, Load Balancing, Cluster Management, Kubernetes Installation, Cluster Security, Access Control, Controller High Availability, Monitoring and Logging, Autoscaling, Advanced Scheduling, Microservices-based Applications, Application Design Patterns, and Deploying Applications on a Kubernetes Cluster.

To achieve scalable and efficient high-performance deep learning, GPU acceleration is a critical requirement for modern workloads.

Designed for intermediate-level technical professionals, this instructor-led live training—available online or onsite—focuses on the configuration, optimization, and execution of GPU-enabled AI workloads within Docker containers.

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

• Develop and execute GPU-capable containers for both training and inference tasks.
• Set up CUDA, drivers, and runtime libraries to support containerized AI pipelines.
• Enhance resource allocation and isolation strategies specifically for GPU-intensive applications.
• Implement scalable, containerized deep learning services within production environments.

Course Delivery Format

• Engaging interactive instruction complemented by practical, real-world demonstrations.
• Practice-oriented exercises centered on GPU-enabled development workflows.
• Direct, hands-on implementation within a live-lab setting.

Customization Opportunities

• To tailor the training to your specific infrastructure or GPU stack, please reach out to discuss bespoke arrangements.

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

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

Upon completing this training, participants will be capable of:

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

Course Format

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

Customization Options

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

In this instructor-led, live training Kenya (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 held in Kenya, participants will learn the essentials of building microservices using Spring Cloud and Docker. Knowledge will be tested through exercises and the incremental development of sample microservices.

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

• Understand the fundamental principles 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.