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Course : Vertex Forecasting and Time Series in PracticeOfficial Course: Preparation for Google Cloud Certification Exams
Practical course - 1d
- 7h00 - Ref. GVF
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 | Understand the basics of time series analysis and forecasting. |
| Prepare and analyze the data to build a predictive model. |
| Train, evaluate, and improve a forecasting model using Vertex AI. |
| Deploy and monitor an end-to-end forecasting solution on Google Cloud. |
Intended audience
Data analysts, data scientists, and ML engineers who want to build high-performance end-to-end forecasting solutions on Google Cloud and automate their workflows.
Prerequisites
Basic knowledge of Python, an understanding of the fundamentals of machine learning, or some initial experience developing machine learning solutions on Google Cloud.
Course schedule
1 Fundamentals of Forecasting and Vertex AI
- Introduction to Forecasting on Google Cloud.
- Time Series Concepts and Sequence Models.
- Analysis of Time Series Data and Principles of Forecasting.
- Forecasting solutions on Google Cloud.
- An overview of Vertex AI Forecasting and its workflow.
2 Data Preparation
- Data ingestion and preparation.
- Data Formats and Requirements for Vertex AI.
- Feature engineering.
- Best practices for data quality and organization.
3 Model Training and Evaluation
- Configuring a forecasting model.
- Training settings (time frame, context window, goals).
- Performance Evaluation and Forecasting Metrics.
- Model optimization and improvement.
4 Deployment, Monitoring, and Use Cases
- Deployment and prediction generation.
- Automation with Vertex AI Pipelines and MLOps.
- Model monitoring, drift, and retraining.
- Implementation of an end-to-end retail use case.
- Summary and Best Practices for Deployment.
PARTICIPANTS
Data analysts, data scientists, and ML engineers who want to build high-performance end-to-end forecasting solutions on Google Cloud and automate their workflows.
PREREQUISITES
Basic knowledge of Python, an understanding of the fundamentals of machine learning, or some initial experience developing machine learning solutions on Google Cloud.
TRAINER QUALIFICATIONS
The experts who lead the training courses are specialists in the subjects covered. They are approved by the publisher and certified for the course. They have also been validated by our teaching teams in terms of both professional knowledge and teaching skills for each course they teach. They have at least three to ten years of experience in their field and hold or have held positions of responsibility in companies.
TERMS AND DEADLINES
Registration must be completed 24 hours before the start of the training course.
ACCESSIBILITY FOR PEOPLE WITH DISABILITIES
Do you have specific accessibility requirements? Contact Ms FOSSE, disability advisor, at the following address: psh-accueil@orsys.fr so that we can assess your request and its feasibility.
Data analysts, data scientists, and ML engineers who want to build high-performance end-to-end forecasting solutions on Google Cloud and automate their workflows.
PREREQUISITES
Basic knowledge of Python, an understanding of the fundamentals of machine learning, or some initial experience developing machine learning solutions on Google Cloud.
TRAINER QUALIFICATIONS
The experts who lead the training courses are specialists in the subjects covered. They are approved by the publisher and certified for the course. They have also been validated by our teaching teams in terms of both professional knowledge and teaching skills for each course they teach. They have at least three to ten years of experience in their field and hold or have held positions of responsibility in companies.
ASSESSMENT TERMS
Assessment of targeted skills prior to training.
Assessment by the participant, at the end of the training course, of the skills acquired during the training course.
Validation by the trainer of the participant's learning outcomes, specifying the tools used: multiple-choice questions, role-playing exercises, etc.
At the end of each training course, ITTCERT provides participants with a course evaluation questionnaire, which is then analysed by our teaching teams. Participants also complete an official evaluation of the publisher.
An attendance sheet for each half-day of attendance is provided at the end of the training course, along with a certificate of completion if the participant has attended the entire session.
Assessment of targeted skills prior to training.
Assessment by the participant, at the end of the training course, of the skills acquired during the training course.
Validation by the trainer of the participant's learning outcomes, specifying the tools used: multiple-choice questions, role-playing exercises, etc.
At the end of each training course, ITTCERT provides participants with a course evaluation questionnaire, which is then analysed by our teaching teams. Participants also complete an official evaluation of the publisher.
An attendance sheet for each half-day of attendance is provided at the end of the training course, along with a certificate of completion if the participant has attended the entire session.
TEACHING AIDS AND TECHNICAL RESOURCES
The teaching resources used are the publisher's official materials and practical exercises.
The teaching resources used are the publisher's official materials and practical exercises.
TERMS AND DEADLINES
Registration must be completed 24 hours before the start of the training course.
ACCESSIBILITY FOR PEOPLE WITH DISABILITIES
Do you have specific accessibility requirements? Contact Ms FOSSE, disability advisor, at the following address: psh-accueil@orsys.fr so that we can assess your request and its feasibility.
This programme is an original creation, developed by the teaching teams at ORSYS Formation. Any reproduction, representation, adaptation or use, in whole or in part, without the prior written authorisation of ORSYS, is strictly prohibited. ORSYS reserves the right to take any action necessary to protect its intellectual property rights.
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This programme is an original creation, developed by the teaching teams at ORSYS Formation. Any reproduction, representation, adaptation or use, in whole or in part, without the prior written authorisation of ORSYS, is strictly prohibited. ORSYS reserves the right to take any action necessary to protect its intellectual property rights.