Google Cloud Big Data and Machine Learning Fundamentals en Français

Google Cloud via Coursera

Go to Course: https://www.coursera.org/learn/gcp-big-data-ml-fundamentals-fr

Introduction

### Course Review: Google Cloud Big Data and Machine Learning Fundamentals en Français #### Overview The "Google Cloud Big Data and Machine Learning Fundamentals en Français" course on Coursera is a comprehensive introduction to understanding the Big Data and Machine Learning tools available on Google Cloud. Designed for both beginners and those looking to enhance their skills, this course covers the entire data lifecycle from ingestion to model deployment. By exploring various Google Cloud products, students gain practical knowledge on how to effectively manage and analyze large datasets through innovative machine learning techniques. #### Course Structure The course is structured into several key modules, each focusing on different aspects of Big Data and Machine Learning on Google Cloud: 1. **Course Introduction**: This initial section welcomes participants and provides an overview of the course objectives, helping learners familiarize themselves with what to expect. 2. **Big Data and Machine Learning on Google Cloud**: This module delves into the core components of the Google Cloud infrastructure. It introduces a wide range of Google Cloud products and services that align with the data-to-AI lifecycle, setting a solid foundation for learners. 3. **Data Engineering for Streaming Data**: Participants will explore Google Cloud's solutions for managing data streams. An end-to-end pipeline is discussed, including data ingestion using Pub/Sub, processing with Dataflow, and data visualization via Looker and Data Studio. 4. **Big Data with BigQuery**: This section dives into BigQuery, which is Google’s serverless data warehouse. It also explores BigQuery ML, introducing key processes and commands for creating custom machine learning models. 5. **Machine Learning Options on Google Cloud**: Offers an exploration of four different approaches to building machine learning models on Google Cloud. This includes an in-depth focus on Vertex AI, which allows users to manage ML projects effectively. 6. **Machine Learning Workflow with Vertex AI**: Here, learners will engage with the three critical phases of a machine learning workflow: data preparation, model training, and model evaluation. There's a practical session where participants can build a machine learning model using AutoML. 7. **Course Summary**: The final section summarizes the course, recapping the topics covered and pointing learners towards additional resources for further study. #### Learning Experience The course is conducted in French, making it an excellent resource for French-speaking learners who are interested in diving into the world of Big Data and Machine Learning. Each section is systematically laid out, making it easy to follow along and absorb the material. The incorporation of practical exercises ensures that participants can apply their knowledge in real-world scenarios. #### Recommendation I highly recommend the "Google Cloud Big Data and Machine Learning Fundamentals en Français" course for anyone looking to enhance their understanding of data and AI in the cloud. Whether you are a novice looking to break into the field or a professional seeking to upgrade your skills, this course provides invaluable insights. The practical elements combined with a solid theoretical foundation will equip you with the tools needed to succeed in managing Big Data and building intelligent machine learning models using Google Cloud. #### Conclusion In a data-driven world, understanding Big Data and Machine Learning is essential, and this course serves as an excellent starting point. By completing it, you will not only gain proficiency in Google Cloud's tools but also prepare yourself for more advanced topics within the realm of data science and AI. Join this course today and take your first steps towards mastering Big Data and Machine Learning with Google Cloud!

Syllabus

Présentation du cours

Cette section accueille les participants au cours Big Data and Machine Learning Fundamentals et leur offr-FRe un aperçu de sa structure et de ses objectifs.

Big data et machine learning sur Google Cloud

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".

Ingénierie des données pour la diffusion de données

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 Data Studio.

Big data avec BigQuery

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.

Options de machine learning sur Google Cloud

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.

Workflow de machine learning avec Vertex AI

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.

Résumé du cours

Cette section revient sur les sujets abordés pendant le cours et oriente les participants vers des ressources supplémentaires qui leur permettront d'approfondir leurs connaissances.