Data Science & AI
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MLOps
Learn Kubeflow from Scratch
A practical, project-based path to Kubeflow in MLOps
By Megha Patel
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Advanced
English
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What you'll learn
- Understand the core concepts of Kubeflow and how they fit together
- Build hands-on projects using Kubeflow that you can add to your portfolio
- Apply Kubeflow to solve real, practical problems in Data Science & AI
- Follow industry best practices and avoid common Kubeflow mistakes
- Gain the confidence to use Kubeflow at work and in interviews
Skills you'll gain
Kubeflow
Practical Projects
Debugging
Best Practices
Problem Solving
MLOps
About this course
Learn Kubeflow the practical way. This Data Science & AI course focuses on doing: you'll work through real examples in MLOps, understand the why behind each technique, and finish with projects for your portfolio. Megha Patel keeps things clear and example-led, so you build genuine, transferable skill. By the end you'll be ready to use Kubeflow confidently at work and in interviews.
Curriculum
Getting Started
- Welcome and what you'll build video · 14:00 ▶ Free preview
- Kubeflow in 10 minutes video · 15:00 ▶ Free preview
- Your first Kubeflow walkthrough video · 16:00
- Hands-on exercise video · 17:00
- Building the project — part 2 video · 06:00
Core Concepts
- Hands-on exercise video · 09:00
- Building the project — part 2 video · 10:00
- Best practices from industry video · 11:00
Hands-On Practice
- Best practices from industry video · 16:00
- A real-world case study video · 17:00
- Recap and where to go next video · 06:00
- Setting up your environment video · 07:00
Building Real Projects
- Welcome and what you'll build video · 11:00
- Kubeflow in 10 minutes video · 12:00
- Your first Kubeflow walkthrough video · 13:00
- Hands-on exercise video · 14:00
- Building the project — part 2 video · 15:00
Going Deeper
- Hands-on exercise video · 06:00
- Building the project — part 2 video · 07:00
- Best practices from industry video · 08:00
Best Practices
- Best practices from industry video · 13:00
- A real-world case study video · 14:00
- Recap and where to go next video · 15:00
- Setting up your environment video · 16:00