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Fixed links to tutorials and codelabs. (#1003)
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title = "Codelabs, Workshops, and Tutorials"
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description = "Recommended end-to-end tutorials, workshops, walk-throughs, and codelabs"
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description = "Recommended end-to-end tutorials, workshops, walk throughs, and codelabs"
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{{% blocks/content-item title="OpenShift Kubeflow Workshop"
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url="https://github.com/AICoE/openshift_kubeflow_workshop" %}}
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Run Kubeflow on Red Hat [OpenShift](https://www.openshift.com/).
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{{% /blocks/content-item %}}
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## Agile Stacks Kubeflow Pipelines tutorials
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{{% blocks/content-item title="Agile Stacks Kubeflow Pipelines Tutorial"
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url="https://www.agilestacks.com/tutorials/ml-pipelines" %}}
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Run Kubeflow Pipelines tutorials on AWS, GCP, or on-prem hardware using [Agile Stacks](https://www.agilestacks.com/).
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Pipeline templates provide step-by-step examples for working with object storage filesystem, Kaniko, Keras, and Seldon.
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{{% /blocks/content-item %}}
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{{% blocks/content-item title="Katacoda scenarios"
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url="https://www.katacoda.com/kubeflow" %}}
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Follow the tutorials to deploy Kubeflow and run a machine learning model.
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{{% /blocks/content-item %}}
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{{% blocks/content-item title="Introduction to Kubeflow Codelab"
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url="https://codelabs.developers.google.com/codelabs/kubeflow-introduction/index.html" %}}
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Run MNIST with Kubeflow on Google Kubernetes Engine.
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{{% /blocks/content-item %}}
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{{% blocks/content-item title="Introduction to Kubeflow Qwiklab"
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url="https://www.qwiklabs.com/catalog_lab/933" %}}
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Run MNIST with resources provided by Qwiklabs.
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{{% /blocks/content-item %}}
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{{% blocks/content-item title="Kubeflow End to End Codelab"
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url="https://codelabs.developers.google.com/codelabs/cloud-kubeflow-e2e-gis/index.html" %}}
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Run GitHub Issue Summarization with Kubeflow on Google Kubernetes Engine.
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{{% /blocks/content-item %}}
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{{% blocks/content-item title="Kubeflow End to End Qwiklab"
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url="https://www.qwiklabs.com/catalog_lab/1046" %}}
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Run GitHub Issue Summarization with resources provided by Qwiklabs.
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{{% /blocks/content-item %}}
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* [ML Pipeline Templates: End-to-end Tutorial](https://www.agilestacks.com/tutorials/ml-pipelines).
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## Google codelabs
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Google Developers Codelabs provide a guided, tutorial, hands-on coding experience.
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* [Introduction to Kubeflow on GKE](https://codelabs.developers.google.com/codelabs/kubeflow-introduction/index.html): Run MNIST with Kubeflow on Google Kubernetes Engine (GKE).
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* [Kubeflow End to End - GitHub Issue Summarization](https://codelabs.developers.google.com/codelabs/cloud-kubeflow-e2e-gis/): Run GitHub Issue Summarization with Kubeflow on GKE.
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* [Kubeflow Pipelines - GitHub Issue
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Summarization](https://codelabs.developers.google.com/codelabs/cloud-kubeflow-pipelines-gis/index.html): Run GitHub Issue Summarization with Kubeflow Pipelines on GKE.
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## Katacoda scenarios
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Follow the [Katacoda tutorials](https://www.katacoda.com/kubeflow) to deploy Kubeflow and run a machine learning model.
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* [Deploying GitHub Issue Summarization with
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Kubeflow](https://www.katacoda.com/kubeflow/scenarios/deploying-github-issue-summarization).
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* [Deploying
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Kubeflow](https://www.katacoda.com/kubeflow/scenarios/deploying-kubeflow).
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* [Deploying Kubeflow with
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ksonnet](https://www.katacoda.com/kubeflow/scenarios/deploying-kubeflow-with-ksonnet).
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* [Deploying Pytorch with
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Kubeflow](https://www.katacoda.com/kubeflow/scenarios/deploy-pytorch-with-kubeflow).
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## OpenShift Kubeflow workshops
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Run Kubeflow on [Red Hat OpenShift](https://www.openshift.com/).
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* [Kubeflow on OpenShift Workshop](https://github.com/AICoE/openshift_kubeflow_workshop).

content/docs/started/getting-started.md

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## Next steps
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* See the [documentation](/docs/) for in-depth instructions on using Kubeflow.
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* Read the [documentation](/docs/) for in-depth instructions on using Kubeflow.
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* Explore the [tutorials and
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codelabs](/docs/examples/codelabs-tutorials/) for learning and trying out Kubeflow.
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* Build machine-learning pipelines with the [Kubeflow Pipelines
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SDK](/docs/pipelines/sdk/sdk-overview/).
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* Explore the self-paced scenarios for learning and trying out Kubeflow:
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* [Codelabs](https://codelabs.developers.google.com/?cat=tensorflow)
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* [Introduction to Kubeflow on Google Kubernetes
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Engine](https://codelabs.developers.google.com/codelabs/kubeflow-introduction/index.html)
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* [Kubeflow End to End: GitHub Issue
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Summarization](https://codelabs.developers.google.com/codelabs/cloud-kubeflow-e2e-gis/index.html)
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* [Kubeflow Pipelines: GitHub Issue
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Summarization](https://codelabs.developers.google.com/codelabs/cloud-kubeflow-pipelines-gis/index.html)
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* [Katacoda](https://www.katacoda.com/kubeflow)
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* [Deploying GitHub Issue Summarization with
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Kubeflow](https://www.katacoda.com/kubeflow/scenarios/deploying-github-issue-summarization)
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* [Deploying
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Kubeflow](https://www.katacoda.com/kubeflow/scenarios/deploying-kubeflow)
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* [Deploying Kubeflow with
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Ksonnet](https://www.katacoda.com/kubeflow/scenarios/deploying-kubeflow-with-ksonnet)
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* [Deploying Pytorch with
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Kubeflow](https://www.katacoda.com/kubeflow/scenarios/deploy-pytorch-with-kubeflow)
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* [Qwiklabs](https://qwiklabs.com/catalog?keywords=kubeflow)
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* [Introduction to Kubeflow on Google Kubernetes
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Engine](https://qwiklabs.com/focuses/960?locale=en&parent=catalog)
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* [Kubeflow End to End: GitHub Issue
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Summarization](https://qwiklabs.com/focuses/1257?locale=en&parent=catalog)

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