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

This instructor-led, live training in Nigeria (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 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 robust containerization platform, delivering consistent, portable, and reproducible environments essential for AI and machine learning workloads.

Designed for intermediate-level professionals, this instructor-led live training—available online or onsite—focuses on packaging ML codebases, dependencies, and models within Docker to ensure reliable development-to-production workflows.

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

• Construct and maintain Docker images specifically optimized for AI and ML applications.
• Encapsulate machine learning pipelines, tools, and their associated dependencies within containers.
• Enhance Docker environments for superior performance and ease of portability.
• Roll out containerized ML services across diverse runtime environments.

Course Delivery Format

• Conceptual demonstrations reinforced through guided discussions.
• Practical hands-on exercises centered on real-world containerization challenges.
• Implementation of strategies using live-lab Docker environments.

Customization Options

• To tailor this training to your specific organizational needs, please reach out to us for arrangement.

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

This instructor-led live training, available either online or on-site, targets intermediate-level professionals seeking to streamline end-to-end AI model delivery workflows using Docker alongside CI/CD platforms.

Upon completing the training, participants will be equipped to:

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

Course Format

• Instructor-led presentations and technical discussions.
• Practical laboratories and hands-on implementation exercises.
• Realistic simulations of CI/CD workflows within a controlled setting.

Customization Options

• If your organization needs tailored pipeline workflows or specific platform integrations, please reach out to us for course customization.

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

Kubernetes has emerged as a leading 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 expertise in Kubernetes environments by preparing 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.

Furthermore, the training focuses on gaining practical experience in Kubernetes Administration; therefore, we recommend participating even if you do not intend to sit for 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 a customized training for this course, please contact us to make arrangements.
• To learn more about CKA certification, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka

The Certified Kubernetes Application Developer (CKAD) program was 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 processes of building, distributing, and running applications within containers.

This instructor-led live training, available both online and onsite, targets engineers who want to deploy and manage software as containers rather than as traditional standalone applications.

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

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

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 Docker, please visit: https://www.docker.com

Discover 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 will acquire the necessary skills to operate modern container platforms and troubleshoot applications across both development and production settings.

In this instructor-led, live training in Nigeria (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 robust containerization platform, enabling the creation of scalable, portable, and reproducible environments essential for modern machine learning systems.

This comprehensive, instructor-led training, available both online and onsite, is tailored for intermediate to advanced technical professionals seeking to operationalize and containerize full-scale ML pipelines using Docker.

By the end of this program, participants will possess the ability to:

• Encapsulate ML training, validation, and inference tasks within containers.
• Architect and manage comprehensive ML pipelines leveraging Docker alongside complementary tools.
• Establish version control, reproducibility, and CI/CD practices for ML components.
• Launch, oversee, and expand ML services within containerized settings.

Instructional Approach

• Engaging lectures complemented by practical live demonstrations.
• Practical exercises dedicated to assembling genuine ML pipeline elements.
• Live laboratory sessions focused on executing end-to-end containerized processes.

Customization Options

• To explore tailored training that aligns with your specific ML infrastructure requirements, please reach out to us for a discussion.

Training Objectives: Acquire 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 caters to participants with diverse experience levels, ensuring a full range of both basic and advanced Kubernetes functionalities. Key concepts covered include Containers, Labels, Controllers, Services, Secrets, Persistent Volumes, Namespaces, Quotas, Container Networking Model, Service Discovery, Scaling, Load Balancing, Cluster Management, Kubernetes Installation, Cluster Security, Access Control, Controller High Availability, Monitoring and Logging, Application Auto-composition, Advanced Scheduling, Microservices-based Applications, Application Design Patterns, and Deploying Applications on a Kubernetes Cluster.

GPU acceleration is critical for executing high-performance deep learning tasks efficiently and at scale.

This instructor-led, live training (available online or onsite) is designed for intermediate-level technical professionals looking to configure, optimize, and manage GPU-enabled AI workloads within Docker containers.

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

• Create and execute GPU-enabled containers for both training and inference.
• Set up CUDA, drivers, and runtime libraries for containerized AI pipelines.
• Enhance resource allocation and isolation for GPU-heavy applications.
• Deploy scalable, containerized deep learning services in production settings.

Course Structure

• Engaging instruction backed by practical, real-world examples.
• Practice sessions centered on GPU-enabled development tasks.
• Practical implementation in a live laboratory setting.

Customization Availability

• For tailored training that aligns with your specific infrastructure or GPU stack, please reach out to us for arrangements.

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

This instructor-led live training (available online or onsite) targets advanced professionals seeking to design and deploy distributed AI inference systems within heterogeneous environments.

Upon completing this training, participants will be able to:

• Develop secure and scalable containerized AI services 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 diverse infrastructure.

Course Format

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

Customization Options

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

In this instructor-led, live training session in Nigeria (onsite or remote), participants will learn how to deploy a collection of sample servers inside containers, then automate, scale, and manage their containerised 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 containerised 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.

During this instructor-led live training in Nigeria, participants will acquire the foundational skills needed to build microservices using Spring Cloud and Docker. Knowledge will be assessed 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.