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

This instructor-led, live training in Argentina (online or onsite) is designed for advanced AI engineers and data scientists with intermediate-to-advanced experience who aim to improve DeepSeek model performance, reduce latency, and deploy AI solutions efficiently using contemporary MLOps practices.

Upon completing 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 Argentina (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 live, instructor-led training in Argentina (available online or onsite) is designed for Kubernetes practitioners aiming to prepare for the CKS exam.

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

This 7-day intensive programme offers a comprehensive, hands-on exploration of designing, deploying, and managing cloud-native applications through contemporary DevOps methodologies.

Attendees will delve into the creation of scalable microservices architectures, optimization of container environments, and management of production workloads using Kubernetes. The curriculum addresses advanced deployment tactics, GitOps-driven automation, and observability standards to guarantee system reliability and high performance.

A significant emphasis is placed on navigating real-world operational hurdles, such as incident response protocols, failure simulation exercises, and root cause analysis. The programme finishes by leveraging AI-powered tools to enhance troubleshooting capabilities and expedite operational decision-making.

Upon completion of the training, participants will possess a solid grasp of how to construct, deploy, monitor, and sustain resilient distributed systems within a Kubernetes ecosystem.

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

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

• Install and configure Helm.
• Build reproducible Kubernetes applications.
• Distribute applications as Helm charts.
• Execute third-party applications provided as Helm charts.
• Manage Helm package releases.

This instructor-led live training, offered in Argentina (either online or onsite), caters to developers and data scientists aiming to build, deploy, and manage machine learning workflows on Kubernetes.

By the end of this program, participants will be capable of:

• Installing and configuring Kubeflow in both on-premise and cloud settings.
• Creating, deploying, and managing ML workflows using Docker containers and Kubernetes.
• Executing full machine learning pipelines across diverse architectures and cloud environments.
• Using Kubeflow to spawn and oversee Jupyter notebooks.
• Building ML training, hyperparameter tuning, and serving workloads on multiple platforms.

This instructor-led, live training in Argentina (online or onsite) is designed for beginner to intermediate software developers and DevOps professionals seeking 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.
• Configure persistent storage and networking solutions for Kubernetes.
• Leverage Minikube for application development, testing, and debugging.

This instructor-led, live training in Argentina (online or onsite) is designed for intermediate developers and DevOps engineers aiming to utilize Minikube within their development workflows.

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 live, instructor-led training in Argentina (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.