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.

This instructor-led live training in Malaysia (delivered online or onsite) is designed for Kubernetes practitioners aiming to prepare for the CKS exam.

Upon completion of this training, participants will have the ability to secure Kubernetes environments and container-based applications across the various 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.

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.

This instructor-led, live training in Malaysia (available online or onsite) is designed for developers and data scientists aiming to build, deploy, and manage machine learning workflows on Kubernetes.

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

• Install and configure Kubeflow in both on-premise and cloud-based environments.
• Architect, deploy, and manage ML workflows leveraging Docker containers and Kubernetes.
• Execute complete machine learning pipelines across various architectures and cloud platforms.
• Leverage Kubeflow to initiate and manage Jupyter notebooks.
• Develop ML training, hyperparameter tuning, and serving workloads across multiple platforms.

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.