Solve Kaggle’s Titanic Problem w/ Kubeflow, Kale and MLOps
The Kaggle Titanic Disaster Survivor Prediction problem is a popular Data Science topic. In this course, you will explore how to solve this problem with Kubeflow. In addition, you’ll learn how the work you are doing is the foundation for an effective and self-sustainable MLOps culture and platform solution that you can undertake at your enterprise. Earn your certificate and share it on LinkedIn to show your continued progression with Kaggle, Kubeflow, and MLOps.
About This Course
This course is approximately 90 minutes long.
In this course, you will:
- Learn about Kaggle.
- Learn about Kubeflow.
- Learn about MLOps.
- Use Jupyter Notebooks in Kubeflow to review the Kaggle Titanic Disaster Survivor Prediction Problem Solution
- Use Kale to convert a Jupyter Notebook into a Kubeflow Pipeline.
- Load the Kubeflow Pipeline Snapshots in new Notebook Servers.
- Perform basic debugging of a Kubeflow Pipeline.
- Relate the activities in this course back to the core tenents of MLOps.
Instructor Led Option
If you would prefer to take the course live, this course is available on a monthly basis with an instructor. If this is your preference, navigate and sign up here .
Certificate of Completion
At the end of this course do not close out the course without earning and sharing your certificate! This certificate can be shared on Linkedin to showcase your new skills.
Arrikto Academy assumes that you have familiarity with popular Data Science concepts and have used some of these philosophies in practice.