1 day course 
Supporting material 
Private Course Credits
Select the pre-paid training investment that’s right for you and help your money stretch a little further with our course credits.
Jellyfish is an award-winning Google Cloud Partner. Our trainers work with Google Cloud on a daily basis, so you'll benefit from the years of industry experience they’ll share with you.
On this course, you'll get hands-on practice through a high-value, real-world use case: predictive customer life value, which uses BigQuery and TensorFlow workflows and then progresses toward training and deploying the model in the cloud with Vertex AI.
You'll learn everything you need to know about the MLOps concept and the considerations behind it, Machine Learning (ML) models and the concept of DevOps in ML, and the importance of operationalizing ML models in a unified AI platform, like Vertex AI.
By the end of the session, you'll have gained a comprehensive understanding of Vertex AI's MLOps capabilities.
This Machine Learning Operations (MLOps) course is available as a private session that can be delivered virtually or at a location of your choice in South Africa.
Course overview
Who should attend:
This course is ideal for aspiring machine learning data scientists, engineers, and analysts, customers, partners, and Googlers who want to streamline and automate their machine learning experimentation and operationalization workflows.
What you'll learn:
By the end of this course, you will be able to:
- Understand (ML) models from an operational perspective
- Understand the concept of DevOps in ML and the importance of operationalizing ML models in a unified AI platform, like Vertex AI
- Understand the MLOps capabilities of Vertex AI
- Understand how Vertex AI helps with the MLOps workflow
Prerequisites
In order to get the most out of this session, you should be proficient in Python; specifically when it comes to topics covered in the Crash Course on Python offered by Google. You should also have prior experience with foundational machine learning concepts and building machine learning solutions on Google Cloud - as covered in the Machine Learning on Google Cloud course.
Course agenda
- Course Introduction
- ML practitioners’ pain points
- The concept of DevOps in ML
- The three phases of the ML lifecycle
- Automating the ML process
- What is Vertex AI and why does a unified platform matter?
- Introduction to MLOps on Vertex AI
- How does Vertex AI help with the MLOps workflow?
- Review the core concepts covered in the course