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

This instructor-led, live training in New Zealand (online or on-site) is designed for advanced-level AI engineers and data scientists with intermediate to advanced experience who aim to enhance DeepSeek model performance, minimise latency, and deploy AI solutions efficiently using modern MLOps practices.

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

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

This instructor-led, live training in New Zealand (online or onsite) is designed for advanced-level platform engineers and DevOps professionals seeking to master scaling applications using microservices and Kubernetes.

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

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

This instructor-led, live training in New Zealand, delivered either online or on-site, is tailored for Kubernetes practitioners aiming to prepare for the CKS exam.

Upon completing this training, participants will understand how to secure Kubernetes environments and container-based applications throughout the various phases of an application's life cycle: build, deployment, and runtime.

This intensive 7-day programme delivers a comprehensive, hands-on exploration into the design, deployment, and operation of cloud-native applications through modern DevOps methodologies.

Attendees will learn to architect scalable microservices solutions, optimise container environments, and manage production workloads using Kubernetes. The curriculum encompasses advanced deployment techniques, GitOps-driven automation, and observability frameworks designed to guarantee system reliability and performance.

A significant emphasis is placed on addressing real-world operational challenges, such as incident response, failure simulation, and root cause analysis. The programme concludes with the integration of AI-powered tools to streamline troubleshooting and expedite operational decision-making.

Upon completion, participants will possess a solid grasp of how to build, deploy, monitor, and maintain resilient distributed systems within a Kubernetes ecosystem.

This instructor-led, live training in New Zealand (online or onsite) is aimed at engineers who wish to use Helm to streamline the process of installing and managing Kubernetes applications.

By the end 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 live, instructor-led training in New Zealand (available online or on-site) is designed for developers and data scientists who aim to build, deploy, and manage machine learning workflows on Kubernetes.

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

• Install and configure Kubeflow in on-premise and cloud environments.
• Construct, deploy, and oversee ML workflows using Docker containers and Kubernetes.
• Run full machine learning pipelines across diverse architectures and cloud platforms.
• Use Kubeflow to generate and manage Jupyter notebooks.
• Develop ML training, hyperparameter tuning, and serving workloads across multiple platforms.

This instructor-led, live training in New Zealand (online or on-site) is designed for beginner to intermediate-level software developers and DevOps professionals who want to learn how to set up and manage a local Kubernetes environment using Minikube.

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

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

This instructor-led, live training in New Zealand (online or on-site) is designed for intermediate-level developers and DevOps engineers who wish to incorporate Minikube into their development workflows.

By the conclusion 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.
• Optimise their development processes by leveraging Minikube's advanced features.
• Apply best practices for local Kubernetes development.

This instructor-led, live training in New Zealand (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 organisation.

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.
• Operationalise the entire Machine Learning process so that it's reproducible and maintainable.