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

Upon completing this training, participants will be capable of:

• Creating custom Docker images.
• Deploying and managing a high volume of Docker applications.
• Evaluating various container orchestration platforms and selecting the optimal solution.
• Establishing a continuous integration pipeline for Docker-based applications.
• Integrating Docker applications into existing continuous integration workflows.
• Implementing security measures for Docker applications.
• Utilizing Kubernetes to deploy and manage diverse environments within a single cluster.
• Securing, scaling, and monitoring a Kubernetes cluster.

This instructor-led, live training in Romania (online or onsite) is aimed at 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 Romania (available online or onsite) is designed for advanced platform engineers and DevOps professionals who wish to master scaling applications using microservices and Kubernetes.

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

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

This instructor-led, live training in Romania, offered online or onsite, targets Kubernetes practitioners aiming to prepare for the CKS exam.

By the end of the training, participants will be equipped to secure Kubernetes environments and container-based applications throughout the application life cycle, covering build, deployment, and runtime stages.

This instructor-led, live training in Romania (online or onsite) is designed for engineers looking to leverage 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 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, available in Romania (online or on-site), targets developers and data scientists looking to build, deploy, and manage machine learning workflows on Kubernetes.

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

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

This instructor-led, live training in Romania (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 basic concepts and architecture of Kubernetes.
• Deploy and manage containers using kubectl and the Minikube dashboard.
• Set up persistent storage and networking solutions for Kubernetes.
• Utilize Minikube for developing, testing, and debugging applications.

This instructor-led, live training in Romania (online or onsite) is designed for intermediate-level developers and DevOps engineers looking to incorporate Minikube into their development workflows.

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

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

This instructor-led, live training in Romania (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.