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

This instructor-led, live training in France (online or onsite) targets advanced AI engineers and data scientists with intermediate-to-advanced expertise who aim to boost DeepSeek model performance, reduce latency, and efficiently deploy AI solutions using contemporary MLOps practices.

By the conclusion of this training, participants will be capable of:

• Optimizing DeepSeek models for efficiency, accuracy, and scalability.
• Applying best practices for MLOps and model versioning.
• Deploying DeepSeek models across cloud and on-premise infrastructure.
• Effectively monitoring, maintaining, and scaling AI solutions.

This instructor-led, live training in France (online or onsite) is aimed at advanced-level platform engineers and DevOps professionals who wish 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.
• 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 (available online or onsite) in France is specifically tailored for Kubernetes practitioners preparing for the CKS examination.

By the end of the program, participants will have acquired the expertise to secure Kubernetes environments and container-based applications across the entire application life cycle, from build and deployment through to runtime.

This seven-day program offers a comprehensive, hands-on journey into designing, deploying, and managing cloud-native applications through modern DevOps practices.

Participants will learn how to design scalable microservices architectures, optimize container environments, and manage production workloads using Kubernetes. The course covers advanced deployment strategies, GitOps-based automation, and observability techniques to ensure system reliability and performance.

A strong emphasis is placed on real-world operational challenges, including incident response, failure simulation, and root cause analysis. The program concludes with the use of AI-powered tools to support troubleshooting and accelerate operational decision-making.

By the end of the training, participants will have a clear understanding of how to build, deploy, monitor, and maintain resilient distributed systems in a Kubernetes-based environment.

This instructor-led, live training in France (online or onsite) is designed for engineers looking to utilize Helm to streamline the installation and management of Kubernetes applications.

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

• Install and configure Helm.
• Create reproducible builds for Kubernetes applications.
• Distribute applications as Helm charts.
• Run third-party applications stored as Helm charts.
• Manage Helm package releases.

This guided live training in France, offered online or on-site, is designed for developers and data scientists seeking to build, deploy, and manage machine learning workflows on Kubernetes.

By the end of the session, participants will be equipped to:

• Install and configure Kubeflow in on-premise and cloud environments.
• Construct, deploy, and manage ML workflows using Docker containers and Kubernetes.
• Execute full machine learning pipelines across diverse architectures and cloud ecosystems.
• Utilize Kubeflow to launch and manage Jupyter notebooks.
• Create ML training, hyperparameter tuning, and serving workloads across various platforms.

This instructor-led, live training in France (online or onsite) is designed for beginner to intermediate 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.
• Understand the fundamental 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 France (online or onsite) is designed for intermediate-level developers and DevOps engineers who wish to integrate Minikube into their development workflows.

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

• Set up and manage a local Kubernetes environment using Minikube.
• Deploy, manage, and debug applications on Minikube effectively.
• Integrate Minikube into continuous integration and deployment pipelines.
• Leverage Minikube's advanced features to streamline their development process.
• Apply industry best practices for local Kubernetes development.

This instructor-led, live training in France (online or onsite) is designed for engineers who wish to evaluate the current approaches and tools available, helping them make informed decisions about the future adoption of MLOps within their organizations.

Upon completing 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 reproducible and maintainable.