Solve Kaggle's OpenVaccine Challenge w/ Kubeflow and MLOps

Data Science, Kubeflow, Kale and MLOps come together in this course based on the Kaggle OpenVaccine Challenge;
4.31 (24 reviews)
Udemy
platform
English
language
Data Science
category
instructor
Solve Kaggle's OpenVaccine Challenge w/ Kubeflow and MLOps
1 271
students
41 mins
content
Aug 2022
last update
FREE
regular price

Why take this course?

🌟 Master Kaggle's OpenVaccine Challenge with Kubeflow and MLOps 🌟

Unlock Your Data Science Potential!

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:

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! 🚀

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Related Topics

4735770
udemy ID
15/06/2022
course created date
07/08/2022
course indexed date
Angelcrc Seven
course submited by
Solve Kaggle's OpenVaccine Challenge w/ Kubeflow and MLOps - Free course | Comidoc