Smart Analytics, Machine Learning, and AI on Google Cloud
Offered By: Google Cloud via Coursera
Course Description
Overview
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
Tags
Related Courses
Google Cloud Fundamentals: Core InfrastructureGoogle via Coursera Google Cloud Big Data and Machine Learning Fundamentals
Google Cloud via Coursera Serverless Data Analysis with Google BigQuery and Cloud Dataflow en Français
Google Cloud via Coursera Essential Google Cloud Infrastructure: Foundation
Google Cloud via Coursera Elastic Google Cloud Infrastructure: Scaling and Automation
Google Cloud via Coursera