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この 1 週間の速習コースは、Data Engineering on Google Cloud Platform 専門講座の以前のコースを基にして作成されています。動画講義、デモ、ハンズオンラボを通して、Google Cloud Platform で Hadoop、Spark、Pig、Hive の各ジョブを実行するためのコンピューティング クラスタを作成、管理する方法を学びます。また、コンピューティング クラスタからクラウド ストレージのさまざまなオプションにアクセスして、Google...
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この 1 週間の速習コースは、Data Engineering on Google Cloud Platform 専門講座の以前のコースを基にして作成されています。動画講義、デモ、ハンズオンラボを通して、Google Cloud Platform で Hadoop、Spark、Pig、Hive の各ジョブを実行するためのコンピューティング クラスタを作成、管理する方法を学びます。また、コンピューティング クラスタからクラウド ストレージのさまざまなオプションにアクセスして、Google の機械学習機能を分析プログラムに統合する方法についても学習します。 ハンズオンラボでは、ウェブ コンソールと CLI を使って Dataproc クラスタを作成、管理し、クラスタを使用して Spark と Pig のジョブを実行します。次に、BigQuery およびストレージと統合する iPython ノートブックを作成し、Spark を活用します。最後に、機械学習 API をデータ分析に統合します。 要件 • Google Cloud Platform Big Data & Machine Learning Fundamentals を修了していること(または同等の経験があること) • Python に関する知識があること
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Helps learners gain experience with Hadoop, Spark, Pig, and Hive, which are used by many Fortune 500 firms
Explores Google Cloud Platform, which is used by many fast-growing startups as well as established companies
Taught by Google Cloud Training, who provide training for Google's own products, which can add confidence in the accurateness of the material
Builds professional skills for individuals new to the field or seeking to explore job opportunities in data engineering

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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 日本語版 with these activities:
Review foundational concepts in Python
Strengthen the foundation by reviewing Python concepts.
Browse courses on Python
Show steps
  • Review online resources or textbooks on Python.
  • Complete practice exercises to test understanding.
Attend a local meetup or conference on Big Data
Connect with professionals in the field and learn about industry trends.
Browse courses on Networking
Show steps
  • Research local meetups or conferences.
  • Attend the event and engage with other attendees.
Creating a Hadoop cluster
Creating a Hadoop cluster will allow you to become more comfortable in a foundational aspect of the course
Browse courses on Hadoop
Show steps
  • Review documentation on creating a Hadoop cluster
  • Create a Hadoop cluster
  • Test your cluster
Six other activities
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Review Hadoop: The Definitive Guide
Review Hadoop basics to strengthen understanding and build a foundation for the course.
Show steps
  • Read chapters 1-3 to understand Hadoop architecture.
  • Install Hadoop on your local machine.
  • Run basic Hadoop commands to familiarize yourself with the system.
Organize and review course materials
Enhance comprehension by organizing and reviewing course resources.
Show steps
  • Gather and organize course materials.
  • Review materials regularly to reinforce concepts.
Create a simple Hadoop cluster for practice
Develop practical skills by creating your own Hadoop cluster.
Browse courses on Hadoop
Show steps
  • Set up a virtual machine or cloud environment.
  • Install Hadoop and configure the cluster.
  • Test the cluster by running a sample job.
Follow online tutorials on Pig and Hive
Expand knowledge of Pig and Hive through guided tutorials.
Browse courses on Pig
Show steps
  • Locate tutorials on Pig and Hive.
  • Follow the tutorials to complete example tasks.
Develop a Spark application to analyze a large dataset
Reinforce Spark concepts by building a practical data analysis application.
Browse courses on Spark
Show steps
  • Gather and preprocess the dataset.
  • Write a Spark program to perform data analysis tasks.
  • Visualize and interpret the analysis results.
Contribute to an open-source Big Data project
Gain real-world experience and contribute to the Big Data community.
Browse courses on Open Source
Show steps
  • Identify open-source Big Data projects.
  • Review the documentation and contribute code or other resources.

Career center

Learners who complete Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform 日本語版 will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists use statistical and machine learning techniques to extract insights from data. They use a variety of tools and technologies, including Hadoop, Spark, Pig, Hive, and Google Cloud Platform. This course teaches the fundamentals of these tools and technologies, and provides hands-on experience in using them to build and manage data pipelines. This course can help you build a foundation for a successful career as a Data Scientist.
Machine Learning Engineer
Machine Learning Engineers build and maintain machine learning models. They use a variety of tools and technologies, including Hadoop, Spark, Pig, Hive, and Google Cloud Platform. This course teaches the fundamentals of these tools and technologies, and provides hands-on experience in using them to build and manage data pipelines. This course can help you build a foundation for a successful career as a Machine Learning Engineer.
Data Engineer
Data Engineers build and manage data pipelines, and develop systems and processes for organizing, storing, and analyzing large amounts of data. They use a variety of tools and technologies, including Hadoop, Spark, Pig, Hive, and Google Cloud Platform. This course teaches the fundamentals of these tools and technologies, and provides hands-on experience in using them to build and manage data pipelines. This course can help you build a foundation for a successful career as a Data Engineer.
Big Data Architect
Big Data Architects design and implement data management solutions for large and complex data sets. They use a variety of tools and technologies, including Hadoop, Spark, Pig, Hive, and Google Cloud Platform. This course teaches the fundamentals of these tools and technologies, and provides hands-on experience in using them to build and manage data pipelines. This course can help you build a foundation for a successful career as a Big Data Architect.
Cloud Architect
Cloud Architects design and implement cloud computing solutions. They use a variety of tools and technologies, including Hadoop, Spark, Pig, Hive, and Google Cloud Platform. This course teaches the fundamentals of these tools and technologies, and provides hands-on experience in using them to build and manage cloud computing solutions. This course can help you build a foundation for a successful career as a Cloud Architect.
Data Analyst
Data Analysts collect, analyze, and interpret data to identify trends and patterns. They use a variety of tools and technologies, including Hadoop, Spark, Pig, Hive, and Google Cloud Platform. This course teaches the fundamentals of these tools and technologies, and provides hands-on experience in using them to collect, analyze, and interpret data. This course can help you build a foundation for a successful career as a Data Analyst.
Business Intelligence Analyst
Business Intelligence Analysts use data to identify business opportunities and solve business problems. They use a variety of tools and technologies, including Hadoop, Spark, Pig, Hive, and Google Cloud Platform. This course teaches the fundamentals of these tools and technologies, and provides hands-on experience in using them to collect, analyze, and interpret data. This course can help you build a foundation for a successful career as a Business Intelligence Analyst.
Software Engineer
Software Engineers design, develop, and maintain software systems. They use a variety of tools and technologies, including Hadoop, Spark, Pig, Hive, and Google Cloud Platform. This course teaches the fundamentals of these tools and technologies, and provides hands-on experience in using them to design, develop, and maintain software systems. This course can help you build a foundation for a successful career as a Software Engineer.
Data Governance Analyst
Data Governance Analysts develop and implement data governance policies and procedures. They use a variety of tools and technologies, including Hadoop, Spark, Pig, Hive, and Google Cloud Platform. This course teaches the fundamentals of these tools and technologies, and provides hands-on experience in using them to develop and implement data governance policies and procedures. This course can help you build a foundation for a successful career as a Data Governance Analyst.
Data Warehouse Engineer
Data Warehouse Engineers design, develop, and maintain data warehouses. They use a variety of tools and technologies, including Hadoop, Spark, Pig, Hive, and Google Cloud Platform. This course teaches the fundamentals of these tools and technologies, and provides hands-on experience in using them to design, develop, and maintain data warehouses. This course can help you build a foundation for a successful career as a Data Warehouse Engineer.
Database Administrator
Database Administrators manage and maintain databases. They use a variety of tools and technologies, including Hadoop, Spark, Pig, Hive, and Google Cloud Platform. This course teaches the fundamentals of these tools and technologies, and provides hands-on experience in using them to manage and maintain databases. This course can help you build a foundation for a successful career as a Database Administrator.
Data Integration Engineer
Data Integration Engineers design, develop, and maintain data integration systems. They use a variety of tools and technologies, including Hadoop, Spark, Pig, Hive, and Google Cloud Platform. This course teaches the fundamentals of these tools and technologies, and provides hands-on experience in using them to design, develop, and maintain data integration systems. This course can help you build a foundation for a successful career as a Data Integration Engineer.
Cloud Data Engineer
Cloud Data Engineers design, develop, and maintain data pipelines in the cloud. They use a variety of tools and technologies, including Hadoop, Spark, Pig, Hive, and Google Cloud Platform. This course teaches the fundamentals of these tools and technologies, and provides hands-on experience in using them to design, develop, and maintain data pipelines in the cloud. This course can help you build a foundation for a successful career as a Cloud Data Engineer.
Data Security Analyst
Data Security Analysts protect data from unauthorized access, use, disclosure, disruption, modification, or destruction. They use a variety of tools and technologies, including Hadoop, Spark, Pig, Hive, and Google Cloud Platform. This course teaches the fundamentals of these tools and technologies, and provides hands-on experience in using them to protect data from unauthorized access, use, disclosure, disruption, modification, or destruction. This course can help you build a foundation for a successful career as a Data Security Analyst.
Data Architect
Data Architects design and develop data management solutions. They use a variety of tools and technologies, including Hadoop, Spark, Pig, Hive, and Google Cloud Platform. This course teaches the fundamentals of these tools and technologies, and provides hands-on experience in using them to design and develop data management solutions. This course can help you build a foundation for a successful career as a Data Architect.

Reading list

We've selected 12 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 日本語版.
Comprehensive guide to Apache Spark, covering its core concepts, programming models, and advanced topics. It can serve as a valuable reference for understanding Spark in depth.
Combines machine learning concepts with Apache Spark, providing practical examples and techniques for integrating machine learning into data analytics pipelines.
Provides a comprehensive guide to building machine learning systems using Python, covering all stages from data preprocessing to model evaluation.
Focuses on data analytics using Google BigQuery, providing a comprehensive guide to its features and applications.
Offers a unique perspective on machine learning, emphasizing intuition and understanding rather than mathematical rigor.
Provides a comprehensive introduction to machine learning concepts and algorithms using the R programming language.
Provides a comprehensive overview of big data analytics, including planning, integration, and case studies. It can provide background knowledge and additional insights beyond the course.
Provides a practical guide to data science using Python, covering data manipulation, analysis, and visualization.
Provides a business-oriented perspective on data science, emphasizing the practical applications and value of data-driven decision-making.
Aims to make data analytics accessible to a wide audience, providing a gentle introduction to key concepts and techniques.

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