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Smart Analytics, Machine Learning, and AI on Google Cloud

Google Cloud via Coursera

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Overview

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Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.

Syllabus

Introduction

In this module, we introduce the course and agenda

Introduction to Analytics and AI

This modules talks about ML options on Google Cloud

Prebuilt ML model APIs for Unstructured Data

This module focuses on using pre-built ML APIs on your unstructured data

Big Data Analytics with Notebooks

This module covers how to use Notebooks

Production ML Pipelines

This module covers building custom ML models and introduces Vertex AI and TensorFlow Hub

Custom Model building with SQL in BigQuery ML

This module covers BigQuery ML

Custom Model Building with Vertex AI AutoML

Custom model building with Vertex AI AutoML

Summary

This module recaps the topics covered in the course

Taught by

Google Cloud Training

Reviews

4.6 rating at Coursera based on 1222 ratings

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