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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.

Introduction to Analytics and AI

This modules talks about ML options on Google Cloud

Module introduction
What is AI?
From ad-hoc data analysis to data-driven decisions
Options for ML models on Google Cloud
QUIZ

Prebuilt ML Model APIs for Unstructured Data

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

Module introduction
Unstructured data is hard
ML APIs for enriching data
Lab Intro: Using the Natural Language API to Classify Unstructured Text
required
LAB: Using the Natural Language API to classify unstructured text: In this lab you’ll learn how to classify text into categories using the Natural Language API
QUIZ

Big Data Analytics with Notebooks

This module covers how to use Notebooks

Module introduction
What’s a Notebook?
BigQuery magic and ties to Pandas
Lab Intro: BigQuery in JupyterLab on Vertex AI
LAB: BigQuery in JupyterLab on Vertex AI 2.5: The purpose of this lab is to show learners how to instantiate a Jupyter notebook running on Google Cloud Platform's AI Platform service.
QUIZ

Production ML Pipelines

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

Module introduction
Ways to do ML on Google Cloud
Vertex AI Pipelines
TensorFlow Hub
Lab Intro: Running Pipelines on Vertex AI
LAB: Running Pipelines on Vertex AI 2.5: In this lab, you learn how to utilize Vertex AI Pipelines to execute a simple Kubeflow Pipeline SDK derived ML Pipeline.
Summary
QUIZ

Custom Model Building with SQL in BigQuery ML

This module covers 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 1 minute
LAB: Predict Bike Trip Duration with a Regression Model in BQML 2.5: In this lab you will use the London bicycles dataset to build a regression model in BQML to predict trip duration.
Lab Intro: Movie Recommendations in BigQuery ML
LAB: Movie Recommendations in BigQuery ML 2.5: In this lab you'll use the MovieLens dataset to build a collaborative filtering model and use it to make predictions.
Summary
QUIZ

Custom Model Building with AutoML

Module introduction
Why AutoML?
AutoML Vision
AutoML Natural Language Processing
AutoML Tables
Summary
QUIZ

Upcoming Trainings

Join our public courses in our Singapore facilities. Private class trainings will be organized at the location of your preference, according to your schedule.

Classroom / Virtual Classroom

06 November 2024