This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
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About this Course
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Try Coursera for BusinessWhat you will learn
Identify the data-to-AI lifecycle on Google Cloud and the major products of big data and machine learning.
Design streaming pipelines with Dataflow and Pub/Sub and dDesign streaming pipelines with Dataflow and Pub/Sub.
Identify different options to build machine learning solutions on Google Cloud.
Describe a machine learning workflow and the key steps with Vertex AI and build a machine learning pipeline using AutoML.
Skills you will gain
- Tensorflow
- Bigquery
- Google Cloud Platform
- Cloud Computing
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessOffered by
Syllabus - What you will learn from this course
Course Introduction
Big Data and Machine Learning on Google Cloud
Data Engineering for Streaming Data
Big Data with BigQuery
Machine Learning Options on Google Cloud
The Machine Learning Workflow with Vertex AI
Course Summary
Reviews
- 5 stars71.61%
- 4 stars23.58%
- 3 stars3.60%
- 2 stars0.58%
- 1 star0.60%
TOP REVIEWS FROM GOOGLE CLOUD BIG DATA AND MACHINE LEARNING FUNDAMENTALS
It is a fun journey to explore the Big Data and ML resource in GCP. And even cooler is you don't need work for a big company or own lots of resource to get your hands dirty to support your learning!
Very good and well thought out.
I just laughed out loud when the translation for "wow this is cool" to Spanish was "wow esto es fresco" (wow, this is a fresco/fresh) Classic google translate.
We have learn't quite a lot of things which is necessary to be a data engineer and how to use GCP as your primary platform to over come the key challenges faced during data engineering life cycle
This was a great course to understand at a high level how to design and create my data ecosystem and how to do it sustainably. Hopefully, next courses provide more in-depth the technical features.
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