Cette formation de spécialisation en ligne d'une durée de cinq semaines présente en pratique comment concevoir et développer des systèmes de traitement des données sur Google Cloud. À travers un ensemble de présentations, de démonstrations et d'ateliers pratiques, les participants apprennent à concevoir des systèmes de traitement de données, à créer des pipelines de données de bout en bout, à analyser des données et à exécuter des tâches de machine learning.
Data Engineer, Big Data and ML on Google Cloud en Français Specialization
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Data Engineer, Big Data and ML on Google Cloud en Français Specialization
Data Engineering on Google Cloud Platform. Boostez votre carrière dans le domaine de l'ingénierie des données
Instructor: Google Cloud Training
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Get in-depth knowledge of a subject
(43 reviews)
Intermediate level
Some related experience required
1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
(43 reviews)
Intermediate level
Some related experience required
1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
What you'll learn
Skills you'll gain
Tools you'll learn
What’s included
Shareable certificate
Add to your LinkedIn profile
Taught in French
24 practice exercises
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from Google Cloud
Specialization - 4 course series
What you'll learn
Faire la différence entre les lacs de données et les entrepôts de données.
Explorer des cas d'utilisation de chaque type de stockage, ainsi que les solutions de lacs et d'entrepôts de données disponibles sur Google Cloud.
Comprendre le rôle des ingénieurs de données et les bénéfices qu'apporte un pipeline de données réussi aux opérations commerciales.
Comprendre pourquoi il est important de procéder à l'ingénierie des données dans un environnement cloud.
Skills you'll gain
Category: Google Cloud Platform
Category: Data Warehousing
Category: Cloud Solutions
Category: Data Architecture
Category: Query Languages
Category: Big Data
Category: SQL
Category: Data Lakes
Category: Data Infrastructure
Category: Cloud Storage
Category: Data Processing
Category: Data Pipelines
What you'll learn
Explorer différentes méthodes de chargement de données (EL, ELT et ETL) et déterminer quand les utiliser.
Exécuter Hadoop sur Dataproc, utiliser Cloud Storage et optimiser les jobs Dataproc.
Créer des pipelines de traitement des données à l'aide de Dataflow.
Gérer des pipelines de données avec Data Fusion et Cloud Composer.
Skills you'll gain
Category: Google Cloud Platform
Category: Data Pipelines
Category: Data Processing
Category: Apache Spark
Category: Cloud Storage
Category: Data Transformation
Category: Dataflow
Category: Data Integration
Category: Serverless Computing
Category: Big Data
Category: Extract, Transform, Load
What you'll learn
Interpréter des cas d'utilisation de l'analyse de flux en temps réel.
Gérer des événements de données à l'aide du service de messagerie asynchrone Pub/Sub.
Écrire des pipelines de flux de données et effectuer des transformations si nécessaire.
Combiner l'utilisation de Dataflow, BigQuery et Pub/Sub pour les flux et l'analyse en temps réel.
Skills you'll gain
Category: Google Cloud Platform
Category: Data Pipelines
Category: Data Processing
Category: Serverless Computing
Category: Data Transformation
Category: Real Time Data
Category: Big Data
Category: Scalability
Category: Data Storage
Category: Query Languages
Category: Public Cloud
What you'll learn
Faire la différence entre le ML, l'IA et le deep learning.
Discuter de l'utilisation des API de ML sur des données non structurées.
Exécuter des commandes BigQuery à partir de notebooks.
Créer des modèles de ML à l'aide de la syntaxe SQL dans BigQuery.
Skills you'll gain
Category: Google Cloud Platform
Category: Applied Machine Learning
Category: Machine Learning
Category: Unstructured Data
Category: Jupyter
Category: Tensorflow
Category: MLOps (Machine Learning Operations)
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Natural Language Processing
Category: Image Analysis
Category: Data Pipelines
Category: Big Data
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
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Frequently asked questions
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
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Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
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