Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform en Français from Coursera

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

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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

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

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Refreshes foundational big data skills necessary to hit the ground running

Browse courses on Data Engineering

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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

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Connects learners with professionals in the field and provides opportunities to learn about the latest trends

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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

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Familiarizes students with the tools and technologies of Google Cloud Platform

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Follow the Data Engineering on Google Cloud Platform tutorials
Complete the hands-on labs to practice using GCP Data Engineering services

Three other activities

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Submit 3 Spark and 3 Pig queries on Dataproc

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Develops proficiency in using Spark and Pig for data analysis on GCP

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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

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Demonstrates proficiency in using BigQuery and Cloud Storage for data analysis

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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

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Applies concepts learned in the course to a real-world data analysis project

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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