Containerized AI & ML Deployment with Docker Training Course

This instructor-led, live training in Botswana (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.

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

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

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

• Create automated pipelines for building and testing AI model containers.
• Implement version control and reproducibility for model lifecycles.
• Integrate automated deployment strategies for AI services.
• Apply CI/CD best practices tailored to 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 organisation requires customized pipeline workflows or platform integrations, please contact us to tailor this course.

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

Kubernetes has emerged as the premier 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 recognised training companies globally in the field of containerisation.

Since 2019, we have also assisted our customers in validating their skills within 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.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

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

The Certified Kubernetes Application Developer (CKAD) programme 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 creation, distribution, and execution of applications within containers.

This instructor-led live training (available online or in person) is tailored for engineers who want to deploy and manage software as containers rather than relying on traditional standalone methods.

Upon completing this training, participants will be capable of:

• Installing and configuring Docker.
• Gaining a solid grasp of and implementing software containerisation.
• Managing applications based on Docker.
• Networking diverse Docker applications and systems.
• Understanding and editing Docker registries.

Course Format

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

Course Customisation Options

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

Learn how to build, deploy, and administer containerised 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 Botswana (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 environments that are reproducible, portable, and scalable for machine learning systems.

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

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

• Encapsulate ML training, validation, and inference workloads within containers.
• Architect and orchestrate holistic ML pipelines leveraging Docker and complementary tools.
• Establish versioning, reproducibility, and CI/CD practices for ML components.
• Deploy, monitor, and scale ML services within containerized infrastructures.

Delivery Format

• Engaging lectures complemented by practical demonstrations.
• Hands-on exercises dedicated to constructing real-world ML pipeline components.
• Live laboratory sessions focused on implementing end-to-end containerized workflows.

Customization Opportunities

• For training tailored to specific ML infrastructure requirements, please reach out to discuss potential solutions.

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 targets participants with varying levels of experience, ensuring a full range of both basic and advanced Kubernetes features. It includes key concepts such as Containers, Labels, Controllers, Services, Secrets, Persistent Data 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-scaling, Advanced Scheduling, Microservices-based Applications, Application Design Patterns, and Application Deployment on a Kubernetes Cluster.

Accelerating high-performance deep learning tasks with GPU support is critical for achieving both scalability and operational efficiency.

This interactive, instructor-led training (available online or onsite) is designed for mid-level technical experts who seek to configure, tune, and execute GPU-driven AI workloads within Docker environments.

Upon completing this course, learners will be equipped to:

• Create and execute GPU-capable containers dedicated to both training and inference tasks.
• Set up CUDA, system drivers, and runtime libraries to support containerized AI processes.
• Enhance resource distribution and isolation specifically for applications demanding heavy GPU processing.
• Launch scalable, container-based deep learning services within live production settings.

Course Delivery Style

• Engaging teaching methods reinforced by practical, real-world examples.
• Task-based practical sessions with a focus on GPU-integrated development.
• Direct implementation activities conducted in a live laboratory setting.

Personalization Possibilities

• To align the training with your specific infrastructure or GPU configuration, please get in touch with us to discuss arrangements.

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

This instructor-led training session (available online or onsite) is designed for advanced professionals seeking to design and deploy distributed AI inference systems within heterogeneous infrastructures.

Upon completing this course, participants will be equipped to:

• Create secure and scalable containerised AI services for multi-site environments.
• Deploy AI inference workloads to cloud platforms, local servers, and edge devices using Docker.
• Utilise 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 within a controlled live-lab setup.

Customisation Options

• To tailor this course to your organisation’s specific infrastructure or use cases, please contact us for customised training solutions.

In this instructor-led, live training session in Botswana (onsite or remotely), participants will learn how to deploy a range of sample servers inside containers and subsequently automate, scale, and manage these containerised servers within a Kubernetes cluster. The training progresses to more advanced topics, guiding participants through the processes of securing, networking, and monitoring a Kubernetes cluster.

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

• Establish and operate a Docker container.
• Deploy containerised databases and servers.
• Set up a Docker and Kubernetes cluster.
• Utilise Kubernetes to deploy and manage various environments within the same cluster.
• Secure, scale, and monitor a Kubernetes cluster.

In this instructor-led, live training in Botswana, participants will learn the core principles of building microservices using Spring Cloud and Docker. Participant knowledge is assessed through exercises and the step-by-step development of sample microservices.

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

• Comprehend the fundamentals of microservices.
• Utilise Docker to build containers for microservice applications.
• Construct and deploy containerised microservices using Spring Cloud and Docker.
• Integrate microservices with discovery services and the Spring Cloud API Gateway.
• Employ Docker Compose for end-to-end integration testing.

This instructor-led, live training in Botswana (online or on-site) targets intermediate-level developers and DevOps engineers who wish to build, deploy, and manage microservices using Spring Cloud and Docker.

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

• Develop microservices using Spring Boot and Spring Cloud.
• Containerize applications with Docker and Docker Compose.
• Implement service discovery, API gateways, and inter-service communication.
• Monitor and secure microservices in production environments.
• Deploy and orchestrate microservices using Kubernetes.