Data Science, Kubeflow, Kale and MLOps come together in this course based on the Kaggle OpenVaccine Challenge;
What you will learn
Articulate the relationship between the Kaggle OpenVaccine Competition and Kubeflow.
Outline the stages of MLOps and explain the value of Kubeflow as it pertains to MLOps.
Use Jupyter Notebooks in Kubeflow to review the Kaggle OpenVaccine Problem Solution.
Define Kubeflow Pipeline using Kale and Jupyter Notebooks hosted on Kubeflow Clusters.
Use Katib to perform Hyperparameter Tuning with Kubeflow Pipelines.
Load Kubeflow Pipeline Snapshots in new Notebook Servers to restore previous state.
Serve the ideal model from a Jupyter Notebook.
Articulate how Machine Learning technologies come together to support MLOps.
Why take this course?
Welcome to an exciting journey into the world of Data Science, where we harness the power of **Kubeflow**, embrace the agility of **Kale**, and build a robust MLOps culture. This course is your key to mastering Kaggle’s OpenVaccine Challenge through real-world application and hands-on learning.
**Course At-A-Glance:**
📚 **What You’ll Learn:**
– The essence of **Kaggle** and its role in the Data Science community.
– How to leverage **Kubeflow** to orchestrate your data workflows with ease.
– The principles and practices that define a successful **MLOps** strategy.
– To transform Jupyter Notebooks into Kubeflow Pipelines using **Kale**.
– The art of hyperparameter tuning with **Katib** to optimize your OpenVaccine model.
– How to deploy and manage your models in production environments.
**Your Learning Path:**
The Kaggle OpenVaccine problem is a complex challenge that invites Data Scientists to predict the distribution of vaccine rollout across different regions, populations, and time scales. In this course, you’ll not only tackle this problem but also understand how your solutions fit into a larger context of enterprise-scale MLOps.
This course is designed as a series of comprehensive articles that will guide you through the process. With approximately 1 to 1.5 hours of content, each article is crafted to enhance your understanding and skills in an incremental, digestible manner.
**Hands-On Learning Steps:**
1. **Dive into Kaggle:** Familiarize yourself with the OpenVaccine problem, its objectives, and how it can be approached from a Data Science perspective.
2. **Explore Kubeflow:** Discover the capabilities of Kubeflow and how it can streamline your machine learning workflows on a Kubernetes cluster.
3. **Understand MLOps:** Learn how MLOps practices can help you automate, monitor, and improve your data science models in production.
4. **Convert Notebooks to Pipelines with Kale:** See how Kale can take your Jupyter Notebooks and transform them into scalable Kubeflow Pipelines.
5. **Optimize Models with Katib:** Utilize Katib for hyperparameter tuning, finding the best parameters for your OpenVaccine model to deliver the most accurate predictions.
6. **Serve Your Model:** Learn how to deploy your optimized model from a Jupyter Notebook to a production environment where it can be used to make real-world impacts.
7. **Relate Back to MLOps:** Understand the critical role that MLOps plays in maintaining and scaling your data science projects, from development to deployment and beyond.
**Prerequisites:**
We expect you to have a foundational understanding of Data Science concepts and some practical experience with these principles. If you’re new to any of these topics, additional resources will be provided to get you up to speed!
**Instructor-Led Option Available!**
For those who prefer a more guided learning experience, this course is also offered as an instructor-led session on a monthly basis. To join this live course, sign up on the Arrikto events page and embark on your learning journey with expert guidance. 🧭
Start your transformation into a master of Data Science and MLOps today! Enroll in this course and take the first step towards becoming an integral part of the Kaggle OpenVaccine Challenge ecosystem, leveraging Kubeflow to make a meaningful impact on the world’s vaccine distribution efforts. Let’s embark on this transformative learning adventure together! 🚀