Google Cloud
Introduction to Vertex Forecasting and Time Series in Practice
Google Cloud

Introduction to Vertex Forecasting and Time Series in Practice

Gain insight into a topic and learn the fundamentals.
Advanced level
Designed for those already in the industry
15 hours to complete
3 weeks at 5 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Advanced level
Designed for those already in the industry
15 hours to complete
3 weeks at 5 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Understand the key concepts and the applications of a sequence model, time series, and forecasting.

  • Identify the options to develop a forecasting model on Google Cloud.

  • Describe the workflow to develop a forecasting model by using Vertex AI.

  • Build a forecasting solution from end-to-end using a retail dataset.

Details to know

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Assessments

7 assignments

Taught in English

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There are 10 modules in this course

This module addresses the reasons to build a forecasting solution on Google Cloud and introduces the learning objectives.

What's included

1 video1 reading

This module provides a theoretical foundation of types of sequence models, time series patterns and analysis, and forecasting notations.

What's included

6 videos1 reading1 assignment

This module introduces two major options to build a forecasting solution on Google Cloud: BigQuery ML and Vertex AI Forecast (AutoML). It also investigates the unique features of Vertex AI Forecast and explores an end-to-end workflow with AutoML.

What's included

7 videos1 reading1 assignment1 app item

This module explores the transformation of original data to the data types and format supported by Vertex AI. It also introduces the different types of features in time series and the best practices for data ingestion.

What's included

6 videos1 reading1 assignment

This module walks learners through the model training and demonstrates the configuration details such as the setup of context window, forecast horizon, and optimization objective.

What's included

7 videos1 reading1 assignment1 app item

This module describes the training data split, demonstrates the evaluation metrics, and recommends the approaches to improve the model performance.

What's included

6 videos1 reading1 assignment

This module demonstrates model prediction, specifically the batch prediction with Vertex AI Forecast. It also explores machine learning operations (MLOps) and the transition from development to production.

What's included

5 videos1 reading1 assignment

This module describes model drift and the approach of model retraining. It also demonstrates the automation of the forecasting workflow by using Vertex AI Pipelines.

What's included

6 videos1 reading1 assignment1 app item

This module describes a use case to build a forecasting solution with Vertex AI Forecast in a retail store. It demonstrates the steps and considerations, walks through a pilot study with two different datasets, and discusses the challenges and lessons.

What's included

7 videos1 reading1 app item

This module addresses the main features of Vertex AI Forecast and summarizes the main topics of each module.

What's included

1 video1 reading

Instructor

Google Cloud Training
Google Cloud
1,636 Courses2,729,636 learners

Offered by

Google Cloud

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