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Google Cloud

Smart Analytics, Machine Learning, and AI on GCP

Google Cloud and Google via Coursera

Overview

Incorporating machine learning into data pipelines increases the ability of businesses to extract insights from their data. This course covers several ways machine learning can be included in data pipelines on Google Cloud Platform depending on the level of customization required. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces AI Platform Notebooks and BigQuery Machine Learning. Also, this course covers how to productionalize machine learning solutions using Kubeflow. Learners will get hands-on experience building machine learning models on Google Cloud Platform using QwikLabs.

Syllabus

  • Introduction
    • This module introduces the course and agenda
  • Introduction to Analytics and AI
    • This modules talks about ML options on GCP
  • Prebuilt ML model APIs for Unstructured Data
    • This module focuses on using pre-built ML APIs on your unstructured data
  • Big Data Analytics with Cloud AI Platform Notebooks
    • This module covers how to use AI Platform Notebooks
  • Productionizing Custom ML Models
    • This module covers building custom ML models and introduces Kubeflow and AI Hub
  • Custom Model building with SQL in BigQuery ML
    • This module covers BigQuery ML
  • Custom Model Building with Cloud AutoML
    • This module introduces Cloud AutoML to build powerful models without coding
  • Summary
    • This module recaps the topics covered in the course

Taught by

Google Cloud Training

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