MLOps on Kubernetes: CI/CD Pipelines for Machine Learning Training Course

This instructor-led, live training in Malaysia (online or onsite) targets advanced-level AI engineers and data scientists with intermediate-to-advanced experience who wish to enhance DeepSeek model performance, minimize latency, and deploy AI solutions efficiently using modern MLOps practices.

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

• Optimize DeepSeek models for efficiency, accuracy, and scalability.
• Implement best practices for MLOps and model versioning.
• Deploy DeepSeek models on cloud and on-premise infrastructure.
• Monitor, maintain, and scale AI solutions effectively.

This instructor-led, live training in Malaysia (online or onsite) is designed for advanced-level platform engineers and DevOps professionals aiming to master application scaling through microservices and Kubernetes.

Upon completing this training, participants will be able to:

• Design and implement scalable microservices architectures.
• Deploy and manage applications on Kubernetes clusters.
• Utilize Helm charts for efficient service deployment.
• Monitor and maintain the health of microservices in production.
• Apply best practices for security and compliance in a Kubernetes environment.

Kubernetes is a widely adopted container orchestration platform used for managing distributed applications at scale.

This instructor-led live training (available online or onsite) is designed for advanced practitioners looking to leverage AI and machine learning techniques to optimize Kubernetes resource usage, scheduling decisions, and autoscaling strategies.

Upon completing this program, participants will be able to:

• Utilize AI/ML models to enhance workload scheduling decisions in Kubernetes.
• Implement intelligent autoscaling using reinforcement learning and metric forecasting.
• Lower infrastructure costs and reduce latency through automated resource optimization.

Course Format

• Instructor-guided technical presentations and in-depth discussions.
• Hands-on lab exercises using real Kubernetes clusters.
• Practical exercises applying AI models to real operational scenarios.

Course Customization Options

• To tailor this course to your platform setup or operational requirements, please contact us for customization.

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 delivering Docker and Kubernetes training since 2015. 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 supported our clients in validating their proficiency 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 focuses on gaining practical experience in Kubernetes Administration; therefore, we recommend participation 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 customized training for this course, please contact us to make arrangements.
• For more information about CKA certification, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka

The Certified Kubernetes Application Developer (CKAD) programme has been established by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), which hosts 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 for Kubernetes.

Additionally, the training focuses on gaining practical experience in Kubernetes application development. Therefore, we recommend participating even if you do not intend to take the CKAD exam.

NobleProg has been delivering Docker & Kubernetes training since 2015. With more than 360 successfully completed training projects, we have become one of the most renowned training companies globally in the field of containerization. Since 2019, we have also assisted our customers in validating their performance in the k8s environment by preparing them and encouraging them to pass the CKA and CKAD exams.

Course Format

• Interactive lecture and discussion.
• Ample 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/

This instructor-led, live training in Malaysia (online or onsite) is aimed at Kubernetes practitioners who wish to prepare for the CKS exam.

By the end of this training, participants will know how to secure Kubernetes environments and container-based applications throughout the different stages of an application's life cycle: build, deployment and runtime.

This seven-day programme offers a comprehensive, hands-on experience in designing, deploying, and operating cloud-native applications using contemporary DevOps methodologies.

Participants will investigate how to architect scalable microservice systems, optimise container environments, and manage production workloads with Kubernetes. The curriculum encompasses advanced deployment techniques, GitOps-driven automation, and observability standards to guarantee system reliability and performance.

Significant emphasis is placed on real-world operational hurdles, including incident response, failure simulation, and root cause analysis. The programme culminates with the utilisation of AI-powered tools to facilitate troubleshooting and expedite operational decision-making.

Upon completion of the training, participants will possess a clear understanding of how to build, deploy, monitor, and maintain resilient distributed systems within a Kubernetes-based environment.

Gain a solid grasp of the fundamentals of containers, Kubernetes, and OpenShift through practical, hands-on training tailored for developers, DevOps engineers, and IT professionals. Participants will learn how to build containerized applications, deploy workloads, manage Kubernetes resources, and leverage OpenShift to streamline modern application delivery in cloud and hybrid environments.

Docker serves as a containerization platform designed to create reproducible, portable, and scalable environments for machine learning systems.

This instructor-led training session, available online or on-site, targets intermediate to advanced technical professionals seeking to containerize and operationalise complete ML pipelines using Docker.

Upon completing this training, participants will gain the ability to:

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

Course Format

• Interactive lectures complemented by practical demonstrations.
• Hands-on exercises centred on constructing real-world ML pipeline components.
• Live-lab implementation of end-to-end containerised workflows.

Course Customization Options

• For training tailored to specific ML infrastructure requirements, please contact us to discuss available options.

This instructor-led, live training in Malaysia (online or onsite) is designed for engineers who want to use Helm to simplify the installation and management of Kubernetes applications.

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

• Install and configure Helm.
• Create reproducible builds of Kubernetes applications.
• Share applications as Helm charts.
• Run third-party applications saved as Helm charts.
• Manage releases of Helm packages.

Kubeflow is an open-source platform designed to streamline building, training, and deploying machine learning workloads on Kubernetes.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to build reliable ML workflows using Kubeflow.

Upon completion of this training, attendees will gain the skills to:

• Navigate the Kubeflow ecosystem and core components.
• Build reproducible workflows with Kubeflow Pipelines.
• Run scalable training jobs on Kubernetes.
• Serve machine learning models efficiently using Kubeflow Serving.

Format of the Course

• Guided presentations and collaborative discussions.
• Hands-on labs with real Kubeflow components.
• Practical exercises to build end-to-end ML workflows.

Course Customization Options

• Customised versions of this training can be arranged to align with your team’s technology stack and project requirements.

This instructor-led, live training in Malaysia (online or in-person) is designed for beginner to intermediate software developers and DevOps professionals looking to learn how to set up and manage a local Kubernetes environment using Minikube.

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

• Install and configure Minikube on their local machine.
• Grasp the fundamental concepts and architecture of Kubernetes.
• Deploy and manage containers using kubectl and the Minikube dashboard.
• Establish persistent storage and networking solutions for Kubernetes.
• Use Minikube for developing, testing, and debugging applications.

This instructor-led, live training in Malaysia (online or on-site) targets intermediate-level developers and DevOps engineers who wish to use Minikube as part of their development workflow.

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

• Set up and manage a local Kubernetes environment using Minikube.
• Understand how to deploy, manage, and debug applications on Minikube.
• Integrate Minikube into their continuous integration and deployment pipelines.
• Optimize their development process using Minikube's advanced features.
• Apply best practices for local Kubernetes development.

This instructor-led live training in Malaysia (online or onsite) is aimed at engineers who wish to evaluate the approaches and tools available today to make an intelligent decision on the path forward in adopting MLOps within their organization.

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

• Install and configure various MLOps frameworks and tools.
• Assemble the right kind of team with the right skills for constructing and supporting an MLOps system.
• Prepare, validate and version data for use by ML models.
• Understand the components of an ML Pipeline and the tools needed to build one.
• Experiment with different machine learning frameworks and servers for deploying to production.
• Operationalize the entire Machine Learning process so that it's reproduceable and maintainable.