Kubeflow Pipelines Courses and Certifications

Bringing ML Workflows to Heterogeneous Cloud Native Machine Learning Platforms Using Intermediate Representation

Explore ML workflow portability using Intermediate Representation in Kubeflow Pipelines v2, enabling cross-platform compatibility and enhanced metadata tracking for efficient machine learning operations.

• YouTube
• 40 minutes
• Self-Paced
• Free Video

Bringing ML Workflows to Heterogeneous Cloud Native Machine Learning Platforms Using Intermediate Representation

Explore ML pipeline portability using Intermediate Representation in Kubeflow Pipelines v2. Learn about new features, orchestration engines, and adapting to different frameworks for efficient machine learning workflows.

• YouTube
• 31 minutes
• Self-Paced
• Free Video

A Deep Dive into Kubeflow Pipelines

Explore Kubeflow Pipelines' architecture and components for executing cloud-native ML workflows on Kubernetes. Gain insights into the platform's inner workings and integration of ML pipeline elements.

• YouTube
• 32 minutes
• Self-Paced
• Free Video

ML Ops Design Patterns with Kubeflow Pipelines

Explore ML Ops design patterns using Kubeflow Pipelines to transition from notebook exploration to production, addressing challenges and implementing effective solutions.

• YouTube
• 20 minutes
• Self-Paced
• Conference Talk

Component Registry for Kubeflow Pipelines

Explore a component registry for Kubeflow Pipelines, enhancing ML workflow collaboration on Kubernetes. Learn how shared components can streamline common tasks and improve efficiency in machine learning projects.

• YouTube
• 29 minutes
• Self-Paced
• Free Video

AIOps for CI with Kubeflow Pipelines

Explore AI4CI, an AIOps tool leveraging Kubeflow Pipelines to monitor builds, predict failures, and create interactive dashboards for improved CI/CD visibility and root cause analysis.

• YouTube
• 26 minutes
• Self-Paced
• Conference Talk

Career Certificate

Machine Learning Operations (MLOps) on Google Cloud

513 ratings at Coursera

Bridge ML prototypes to production on Google Cloud: manage features with Vertex AI Feature Store, evaluate predictive and generative models, and orchestrate pipelines with the Kubeflow SDK.

• Coursera
• 4 weeks, 4 hours a week
• Self-Paced
• Paid Course
• 4 courses

LLMOps

39 ratings at Coursera

Build an LLMOps pipeline: transform BigQuery data for supervised instruction tuning, version models, and run Kubeflow Pipelines on Google Cloud to deploy a Python Q&A chatbot.

• Coursera
• 1 hour 3 minutes
• Self-Paced
• Free Online Course

Orchestrate ML Workflows with Vertex AI Pipelines

Orchestrate ML workflows on Google Cloud: build MLOps pipelines with the no-code Template Gallery, Kubeflow Pipelines SDK components, DAGs and lineage, plus the Data Science Agent.

• Coursera
• 6 weeks, 1 hour a week
• Self-Paced
• Paid Course

Packt

Real-world End to End Machine Learning Ops on Google Cloud

Manage the ML model lifecycle on Google Cloud: build CI/CD pipelines with Cloud Run, orchestrate training with Airflow and Kubeflow, and tune and version models in Vertex AI.

• Coursera
• 8 weeks, 1 hour a week
• Self-Paced
• Paid Course

Scaling ML Pipelines with KALE - The Kubeflow Automated Pipeline Engine

Discover KALE, the Kubeflow Automated Pipeline Engine, for scaling ML pipelines. Learn how to transform Jupyter Notebook experiments into production-grade pipelines for efficient model training and real-time serving.

• YouTube
• 25 minutes
• Self-Paced
• Conference Talk

MLOps World: Machine Learning in Production

Building Pipelines with Kubeflow - Hands-on Workshop

Discover Kubeflow pipelines: create environments, build and upload pipelines, and set up retraining schedules in this hands-on workshop for MLOps practitioners.

• YouTube
• 3 hours 43 minutes
• Self-Paced
• Free Video

Operating Deep Learning Pipelines Anywhere Using Kubeflow

Explore building and operating production-grade deep learning pipelines using Kubeflow, covering data preparation, storage, automation, and infrastructure management for multiple tenants.

• YouTube
• 39 minutes
• Self-Paced
• Conference Talk

MLOps World: Machine Learning in Production

Creating Machine Learning Retraining Pipelines with Kubeflow and Kubernetes

Develop ML retraining pipelines using Kubernetes and Kubeflow. Master advanced techniques for efficient model updates and deployment in production environments.

• YouTube
• 2 hours 5 minutes
• Self-Paced
• Free Video

Canonical Ubuntu

Building Machine Learning Pipelines with Kubeflow

Master building ML pipelines using Kubeflow's components, from key considerations to best practices, and learn effective implementation strategies for scaling machine learning projects.

• YouTube
• 52 minutes
• Self-Paced
• Free Video