Course Overview
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.
Moyens d'évaluation :
- Quiz pré-formation de vérification des connaissances (si applicable)
- Évaluations formatives pendant la formation, à travers les travaux pratiques réalisés sur les labs à l’issue de chaque module, QCM, mises en situation…
- Complétion par chaque participant d’un questionnaire et/ou questionnaire de positionnement en amont et à l’issue de la formation pour validation de l’acquisition des compétences
Who should attend
Data Engineers
Prerequisites
Participants should have completed the Google Cloud Big Data and Machine Learning Fundamentals course or have equivalent experience.
Course Objectives
- Differentiate between ML, AI and deep learning.
- Discuss the use of ML API’s on unstructured data.
- Execute BigQuery commands from notebooks.
- Create ML models by using SQL syntax in BigQuery.
- Create ML models without coding by using AutoML
Moyens Pédagogiques :