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Vertex AI Forecasting: Advanced Time Series Analysis
Master time series forecasting with Google Cloud's Vertex AI. Learn end-to-end workflow from data prep to model deployment and monitoring.
Course Cost
₹ 2,699
Advanced
Skill Level
15 Hours
Self-paced lessons
This advanced course introduces building forecasting solutions with Google Cloud's Vertex AI. It covers sequence models, time series analysis, and forecasting fundamentals before diving into practical implementation. Students learn the end-to-end workflow: from data preparation and feature engineering to model training, evaluation, deployment, and monitoring using Vertex AI. The course explores both BigQuery ML and Vertex AI Forecast options, with a focus on AutoML capabilities. Hands-on labs provide practical experience in building demand forecasting models, training with Vertex AI Forecast, and creating automated pipelines with Vertex AI Python SDKs. A retail use case demonstrates real-world application, challenges, and best practices. This course is ideal for professionals seeking to leverage Google Cloud's advanced AI capabilities for time series forecasting.
English
What you'll learn
Understand key concepts and applications of sequence models, time series, and forecasting
Identify options to develop forecasting models on Google Cloud
Describe the workflow to develop a forecasting model using Vertex AI
Build an end-to-end forecasting solution using a retail dataset
Prepare and transform data for time series forecasting
Configure and train models using Vertex AI Forecast
Evaluate model performance and implement improvement strategies
Deploy models and make batch predictions
Skills you'll gain
This course includes:
174 Minutes PreRecorded video
7 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There are 10 modules in this course
This comprehensive course provides an in-depth exploration of time series forecasting using Google Cloud's Vertex AI. Starting with foundational concepts in sequence models and time series analysis, the course progresses through the entire lifecycle of building a forecasting solution. Students learn to prepare and engineer data for time series models, train models using Vertex AI Forecast, evaluate their performance, and deploy them for predictions. The curriculum covers advanced topics such as context window optimization, handling different optimization objectives, and implementing MLOps practices with Vertex AI Pipelines. Through hands-on labs, learners gain practical experience in using BigQuery ML for demand forecasting, training models with Vertex AI Forecast, and building end-to-end forecasting pipelines. The course culminates with a real-world retail use case, demonstrating the application of learned concepts and discussing challenges and best practices in implementing forecasting solutions.
Introduction
Module 1 · 32 Minutes to complete
Time series and forecasting fundamentals
Module 2 · 1 Hours to complete
Forecasting options on Google Cloud
Module 3 · 2 Hours to complete
Data preparation
Module 4 · 1 Hours to complete
Model training
Module 5 · 3 Hours to complete
Model evaluation
Module 6 · 53 Minutes to complete
Model deployment
Module 7 · 46 Minutes to complete
Model monitoring
Module 8 · 3 Hours to complete
Vertex forecasting in retail
Module 9 · 55 Minutes to complete
Summary
Module 10 · 38 Minutes to complete
Fee Structure
Payment options
Financial Aid
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Faculties
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