We may earn an affiliate commission when you visit our partners.
Course image
Google Cloud Training
Ce cours intensif, d'une durée d'une semaine, se base sur de précédents cours de la spécialisation Data Engineering on Google Cloud Platform. À travers un ensemble de conférences vidéo, de démonstrations et d'ateliers pratiques, vous allez apprendre à créer et à gérer des clusters informatiques pour exécuter des tâches Hadoop, Spark, Pig et Hive sur Google Cloud Platform.Vous apprendrez également à accéder à diverses options de stockage dans le cloud à partir de leurs clusters de calcul et à intégrer les fonctionnalités de machine learning de Google à leurs programmes d'analyse. Lors des ateliers pratiques, vous allez créer et...
Read more
Ce cours intensif, d'une durée d'une semaine, se base sur de précédents cours de la spécialisation Data Engineering on Google Cloud Platform. À travers un ensemble de conférences vidéo, de démonstrations et d'ateliers pratiques, vous allez apprendre à créer et à gérer des clusters informatiques pour exécuter des tâches Hadoop, Spark, Pig et Hive sur Google Cloud Platform.Vous apprendrez également à accéder à diverses options de stockage dans le cloud à partir de leurs clusters de calcul et à intégrer les fonctionnalités de machine learning de Google à leurs programmes d'analyse. Lors des ateliers pratiques, vous allez créer et gérer des clusters Dataproc via la console Web et la CLI, et vous utiliserez les clusters pour exécuter des tâches Spark et Pig. Vous créerez ensuite des notebooks iPython qui s'intègrent à BigQuery et à l'espace de stockage, et vous utiliserez Spark. Enfin, vous intégrerez les API de machine learning à votre analyse de données. Prérequis • Avoir suivi la formation Google Cloud Platform Big Data & Machine Learning Fundamentals (ou disposer d'une expérience équivalente) • Disposer de quelques notions de Python
Enroll now

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches application of machine learning in data analytics, which enhances learners' analytical capabilities
Facilitates integration of cloud storage with computing clusters, a key aspect of modern data analytics
Provides a comprehensive overview of various data storage options on Google Cloud Platform
Emphasizes hands-on learning through practical workshops, fostering practical skills in data engineering
Requires prerequisite knowledge in Google Cloud Platform Big Data and Machine Learning Fundamentals, limiting accessibility for beginners

Save this course

Save Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform en Français to your list so you can find it easily later:
Save

Reviews summary

Structured cloud data in french

This advanced one-week course is designed for students who have taken previous courses in the Data Engineering track on Google Cloud Platform. With video lectures, demonstrations, and hands-on labs, you will learn to create and manage clusters for running Hadoop, Spark, Pig, and Hive jobs on Google Cloud Platform. You will also access cloud storage options from your compute clusters and incorporate Google machine learning capabilities into your analytics. In the hands-on labs, you will create and manage Dataproc clusters with the web console and CLI, and run Spark and Pig jobs on your clusters. You will then create IPython notebooks that connect to BigQuery and Cloud Storage, and use Spark. Finally, you will integrate machine learning APIs into your data analysis. Prerequisites - Google Cloud Platform Big Data & Machine Learning Fundamentals course (or equivalent experience). - Some experience with Python.
Valuable hands-on experience
"...In the hands-on labs, you will create and manage Dataproc clusters with the web console and CLI, and run Spark and Pig jobs on your clusters..."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform en Français with these activities:
Review big data concepts
Refreshes foundational big data skills necessary to hit the ground running
Browse courses on Data Engineering
Show steps
  • Review key concepts of Hadoop, Spark, Pig, and Hive
  • Read documentation on Google Cloud Platform Big Data services
Attend a Google Cloud Platform Data Engineering Meetup
Connects learners with professionals in the field and provides opportunities to learn about the latest trends
Show steps
  • Find a Google Cloud Platform Data Engineering Meetup near you
  • RSVP to attend the Meetup
  • Attend the Meetup and network with other attendees
Complete Google Cloud Platform Data Engineering tutorials
Familiarizes students with the tools and technologies of Google Cloud Platform
Show steps
  • Follow the Data Engineering on Google Cloud Platform tutorials
  • Complete the hands-on labs to practice using GCP Data Engineering services
Three other activities
Expand to see all activities and additional details
Show all six activities
Submit 3 Spark and 3 Pig queries on Dataproc
Develops proficiency in using Spark and Pig for data analysis on GCP
Show steps
  • Create a Dataproc cluster
  • Submit a Spark query to the cluster
  • Submit a Pig query to the cluster
Build a notebook that integrates BigQuery and Cloud Storage
Demonstrates proficiency in using BigQuery and Cloud Storage for data analysis
Show steps
  • Create an IPython notebook
  • Connect the notebook to BigQuery
  • Connect the notebook to Cloud Storage
  • Write a Spark program that reads data from BigQuery and Cloud Storage
Develop a data analysis pipeline using Google Cloud Platform
Applies concepts learned in the course to a real-world data analysis project
Show steps
  • Define the scope and goals of the project
  • Gather data from multiple sources
  • Clean and prepare the data
  • Analyze the data using Spark and Pig
  • Visualize and interpret the results

Career center

Learners who complete Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform en Français will develop knowledge and skills that may be useful to these careers:
Cloud Data Engineer
Cloud Data Engineers design, build, and manage data pipelines in the cloud. This course provides hands-on experience in creating and managing clusters for executing big data tasks on Google Cloud Platform, which is essential for Cloud Data Engineers.
Data Scientist
Data Scientists use data to solve business problems and create new products and services. The integration of Google's machine learning capabilities into this course may be useful in helping to build skills that are essential to the role.
Big Data Architect
Big Data Architects design and build big data solutions. This course provides foundational skills in working with big data frameworks such as Hadoop, Spark, and Hive on Google Cloud Platform, which could be valuable for Big Data Architects.
Machine Learning Engineer
Machine Learning Engineers build, deploy, and maintain machine learning models. The integration of Google's machine learning capabilities into this course may be useful in helping to build skills that are essential to the role.
Data Architect
Data Architects design and build data systems. This course provides a comprehensive overview of big data technologies and how to use them on Google Cloud Platform, which is valuable for Data Architects who work with big data.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical techniques to analyze financial data. The integration of Google's machine learning capabilities into this course may be useful in building skills that are essential to the role.
Data Engineer
Data Engineers build, maintain, and manage data pipelines that deliver data to data scientists and business analysts. As data engineering projects typically use big data frameworks such as Hadoop, Spark, and Hive, this course may be useful in helping to build foundational skills.
Cloud Architect
Cloud Architects design, build, and manage cloud computing solutions. This course covers how to create and manage clusters for executing big data tasks on Google Cloud Platform, which could be valuable for Cloud Architects who work with big data.
Database Administrator
Database Administrators maintain and manage databases. This course covers how to access various cloud storage options from computing clusters, which could be valuable for Database Administrators who work with big data.
Operations Research Analyst
Operations Research Analysts use mathematical and analytical methods to solve business problems. While this course is not directly focused on operations research, it may be useful in building a foundation in big data technologies commonly used by Operations Research Analysts.
Software Engineer
Software Engineers design, develop, and maintain software systems. While this course is not directly focused on software engineering, it may be useful in building a foundation in big data technologies commonly used by Software Engineers.
Business Intelligence Analyst
Business Intelligence Analysts help businesses make better decisions by providing insights from data. While this course is not specifically focused on business intelligence, it may be useful in building a foundation in big data technologies frequently used by Business Intelligence Analysts.
Research Scientist
Research Scientists conduct research in various scientific fields. This course may be useful in building a foundation in big data technologies increasingly used by Research Scientists.
Data Analyst
Data Analysts collect, clean, and analyze data to help businesses make informed decisions. While this course is not directly focused on data analysis, it may be useful in helping to build a foundation in big data technologies that are commonly used by Data Analysts.
Statistician
Statisticians collect, analyze, and interpret data. This course may be useful in helping to build a foundation in big data technologies that are increasingly used by Statisticians.

Reading list

We've selected nine books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform en Français.
Is an excellent resource for learning how to use Spark for machine learning. It covers a wide range of topics, from basic concepts to advanced techniques.
Comprehensive guide to Spark, covering everything from the basics to advanced topics such as performance tuning and machine learning.
Provides a comprehensive overview of predictive modeling, covering a wide range of topics from data preparation to model evaluation. It good resource for learners who want to understand the principles and practices of predictive modeling.
This textbook provides a more theoretical approach to machine learning, covering the mathematical foundations and algorithms. It good resource for learners who want to understand the theory behind machine learning models and algorithms.
This textbook provides a practical approach to machine learning, with step-by-step instructions for building machine learning models using popular Python libraries. It good resource for learners who want to get started with practical machine learning.
This tutorial comprehensive guide to using Python for data analysis. It covers a wide range of topics, from data cleaning to data visualization. It is also widely used and can serve as a helpful reference text.
Comprehensive guide to Pig, covering everything from the basics to advanced topics such as data processing and optimization.
Is good for bridging this course material to advanced machine learning topics. It is less directly relevant than other materials but can provide good context and future directions for learners.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform en Français.
Elastic Cloud Infrastructure: Containers and Services en...
Most relevant
Architecting with Google Kubernetes Engine: Workloads en...
Most relevant
Reliable Cloud Infrastructure: Design and Process en...
Most relevant
Building Resilient Streaming Systems on Google Cloud...
Most relevant
Hybrid Cloud Infrastructure Foundations with Anthos en...
Most relevant
Les outils du métier : Linux et SQL
Most relevant
Getting Started With Application Development en Français
Most relevant
Google Cloud Product Fundamentals en Français
Most relevant
Google Cloud Fundamentals: Core Infrastructure en Français
Most relevant
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2024 OpenCourser