Ce cours présente les produits et services Google Cloud pour le big data et le machine learning compatibles avec le cycle de vie "des données à l'IA". Il explore les processus, défis et avantages liés à la création d'un pipeline de big data et de modèles de machine learning avec Vertex AI sur Google Cloud.
Google Cloud Big Data and Machine Learning Fundamentals en Français
Google Cloud Big Data and Machine Learning Fundamentals en Français
This course is part of Data Engineer, Big Data and ML on Google Cloud en Français Specialization
Instructor: Google Cloud Training
2,855 already enrolled
Included with 
Gain insight into a topic and learn the fundamentals.
4.3
(44 reviews)
Intermediate level
Some related experience required
10 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Comprendre le cycle de vie "des données à l'IA" sur Google Cloud ainsi que les principaux produits de big data et de machine learning
Créer des pipelines de traitement par flux avec Dataflow et Pub/Sub
Analyser le big data à grande échelle avec BigQuery
Identifier différentes options pour créer des solutions de machine learning sur Google Cloud
Details to know
Shareable certificate
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Assessments
5 assignments
Taught in French
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This course is part of the Data Engineer, Big Data and ML on Google Cloud en Français Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 7 modules in this course
Cette section accueille les participants au cours Big Data and Machine Learning Fundamentals et leur offre un aperçu de sa structure et de ses objectifs.
What's included
2 videos1 reading
Cette section aborde les composants clés de l'infrastructure Google Cloud. Elle présente un grand nombre des produits et services Google Cloud pour le big data et le machine learning, tous compatibles avec le cycle de vie "des données à l'IA".
What's included
10 videos1 reading1 assignment1 app item
Cette section présente la solution de Google Cloud pour gérer les flux de données. Elle examine un pipeline de bout en bout, y compris l'ingestion de données avec Pub/Sub, le traitement des données via Dataflow, et la visualisation des données avec Looker et Looker Studio.
What's included
9 videos1 reading1 assignment1 app item
Cette section présente BigQuery, l'entrepôt de données sans serveur entièrement géré de Google. Elle aborde également BigQuery ML, ainsi que les processus et les commandes clés permettant de créer des modèles de machine learning personnalisés.
What's included
9 videos1 reading1 assignment1 app item
Cette section explore quatre options différentes pour créer des modèles de machine learning sur Google Cloud. Elle présente également Vertex AI, la plate-forme unifiée de Google permettant de créer des projets de ML et de gérer leur cycle de vie.
What's included
8 videos1 reading1 assignment
Cette section se concentre sur les trois phases clés d'un workflow de machine learning dans Vertex AI : préparation des données, entraînement du modèle et évaluation du modèle. Les participants ont l'occasion de s'entraîner à créer un modèle de machine learning avec AutoML.
What's included
8 videos1 reading1 assignment1 app item
Cette section revient sur les sujets abordés pendant le cours. Il oriente également les participants vers des ressources supplémentaires qui leur permettront d'approfondir leurs connaissances.
What's included
1 video
Instructor
Instructor ratings
4.4 (15 ratings)Offered by
Recommended if you're interested in Machine Learning
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MM
4
Reviewed on Aug 30, 2019
Les cours sont bien faits. Merci de mettre plus de taches dans les travaux pratiques. Enfin le code pySpark dans l'un des ateliers n'est pas expliqué du tout.
BG
4
Reviewed on Dec 3, 2020
Pity there are so many bugs in the quizz (and for months, it seems!), the content in itself is very good, imho.
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