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Smart Analytics, Machine Learning, and AI on Google Cloud - Locales

Google via Google Cloud Skills Boost

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Overview

This course, Smart Analytics, Machine Learning, and AI on Google Cloud - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Smart Analytics, Machine Learning, and AI on Google Cloud. 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 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 Notebooks and BigQuery machine learning (BigQuery ML). 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 using QwikLabs.

Syllabus

  • Introduction
    • Course Introduction
  • Introduction to Analytics and AI
    • Module introduction
    • What is AI?
    • From ad-hoc data analysis to data-driven decisions
    • Options for ML models on Google Cloud
    • Introduction to Analytics and AI
  • Prebuilt ML Model APIs for Unstructured Data
    • Module introduction
    • Unstructured data is hard
    • ML APIs for enriching data
    • Lab Intro: Using the Natural Language API to Classify Unstructured Text
    • Using the Natural Language API to classify unstructured text
    • Prebuilt ML model APIs for Unstructured Data
  • Big Data Analytics with Notebooks
    • Module introduction
    • What’s a Notebook?
    • BigQuery magic and ties to Pandas
    • Lab Intro: BigQuery in JupyterLab on Vertex AI
    • BigQuery in JupyterLab on Vertex AI 2.5
    • Big Data Analytics with Notebooks
  • Production ML Pipelines with Kubeflow
    • Module introduction
    • Ways to do ML on Google Cloud
    • Kubeflow
    • AI Hub
    • Lab Intro: Running ML Pipelines on Kubeflow
    • Running Pipelines on Vertex AI 2.5
    • Summary
    • Productionizing Custom ML Models
  • Custom Model building with SQL in BigQuery ML
    • Module introduction
    • BigQuery ML for Quick Model Building
    • Supported models
    • Lab Intro: Predict Bike Trip Duration with a Regression Model in BigQuery ML
    • Predict Bike Trip Duration with a Regression Model in BQML 2.5
    • Lab Intro: Movie Recommendations in BigQuery ML
    • Movie Recommendations in BigQuery ML 2.5
    • Summary
    • Custom Model building with SQL in BigQuery ML
  • Custom Model Building with AutoML
    • Module introduction
    • Why AutoML?
    • AutoML Vision
    • AutoML Natural Language Processing
    • AutoML Tables
    • Summary
    • Custom Model Building with AutoML
  • Summary
    • Course Summary
  • Course Resources
    • Smart Analytics, Machine Learning, and AI on Google Cloud

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