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Google Cloud Training

Este curso intensivo de uma semana baseia-se nos cursos anteriores da especialização Data Engineering on Google Cloud Platform. Por meio de videoaulas, demonstrações e laboratórios práticos, você aprenderá a criar e gerenciar clusters de computação para executar jobs do Hadoop, Spark, Pig e/ou Hive no Google Cloud Platform.Você também aprenderá a acessar várias opções de armazenamento em nuvem dos clusters de computação e integrar os recursos de machine learning do Google aos respectivos programas de análise.

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Este curso intensivo de uma semana baseia-se nos cursos anteriores da especialização Data Engineering on Google Cloud Platform. Por meio de videoaulas, demonstrações e laboratórios práticos, você aprenderá a criar e gerenciar clusters de computação para executar jobs do Hadoop, Spark, Pig e/ou Hive no Google Cloud Platform.Você também aprenderá a acessar várias opções de armazenamento em nuvem dos clusters de computação e integrar os recursos de machine learning do Google aos respectivos programas de análise.

Nos laboratórios práticos, você criará e gerenciará os clusters do Dataproc usando o console da Web e a CLI e usará o cluster para executar jobs do Spark e Pig. Depois você criará notebooks iPython que são integrados ao BigQuery e ao armazenamento e utilizará o Spark. Por fim, você integrará as APIs de machine learning à análise de dados.

Pré-requisitos

• Noções básicas de Big Data e Machine Learning do Google Cloud Platform (ou experiência equivalente)

• Algum conhecimento de Python

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What's inside

Syllabus

Módulo 1: introdução ao Cloud Dataproc
Este curso intensivo de uma semana é uma continuação dos cursos anteriores da especialização Data Engineering on Google Cloud Platform. Por meio de uma combinação de palestras em vídeo, demonstrações e laboratórios práticos, você aprenderá a criar e gerenciar clusters de computação para executar jobs do Hadoop, Spark, Pig e/ou Hive no Google Cloud Platform. Você também verá como acessar várias opções do Cloud Storage a partir dos seus clusters de computação, além de integrar recursos de aprendizado de máquina do Google aos seus programas de análise.
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Módulo 2: como executar jobs do Dataproc
Módulo 3: como usar o GCP
Módulo 4: como analisar dados não estruturados

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches the foundational skills required for Google Cloud Platform, which is widely used and trusted in industry for enterprise solutions
Develops expertise in using Google Cloud Platform, which is valuable for professional development and building strong foundations in this field
Taught by Google Cloud Training, who are recognized for their expertise and authority in the field of Google Cloud Platform
Offers a hands-on learning experience through practical labs, which allows for better understanding and skill development
Requires prior knowledge in Big Data and Machine Learning, which may limit accessibility for complete beginners
Focuses on Cloud Dataproc, which is a specific technology within Google Cloud Platform, limiting the scope of the course

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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 em Português Brasileiro with these activities:
Review Apache Hadoop Basics
Reinforce your foundational knowledge of Hadoop to prepare for the upcoming course.
Browse courses on Apache Hadoop
Show steps
  • Read through Hadoop tutorials and documentation
  • Take practice quizzes and answer discussion questions on Hadoop fundamentals
Explore GCP's Cloud DataProc Documentation
Gain a deeper understanding of Cloud DataProc's features and capabilities to enhance your learning experience.
Browse courses on Google Cloud Dataproc
Show steps
  • Read through Cloud DataProc's documentation and tutorials
  • Follow along with guided walkthroughs on using Cloud DataProc
  • Experiment with Cloud DataProc's features in a sandbox environment
Practice Spark and Pig Scripting
Sharpen your skills in Spark and Pig scripting to enhance your ability to analyze and manipulate large datasets.
Browse courses on Apache Spark
Show steps
  • Solve coding challenges on platforms like HackerRank or LeetCode
  • Work through practice exercises on Spark and Pig scripting
  • Create your own Spark and Pig scripts for data analysis tasks
Three other activities
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Show all six activities
Explore Integrations with Google Machine Learning APIs
Delve into the integration possibilities between Cloud DataProc and Google Machine Learning APIs to expand your data analysis capabilities.
Show steps
  • Read documentation and tutorials on integrating Google Machine Learning APIs
  • Follow along with guided examples of API integration
  • Develop your own projects that leverage Google Machine Learning APIs with Cloud DataProc
Create a Data Analysis Pipeline with Cloud DataProc and Spark
Apply your knowledge to build a complete data analysis pipeline that leverages the capabilities of Cloud DataProc and Spark.
Show steps
  • Design your data analysis pipeline
  • Implement the pipeline using Cloud DataProc and Spark
  • Test and evaluate the performance of your pipeline
Contribute to Open Source Data Analytics Projects
Engage in real-world data analytics projects and contribute to the broader community while reinforcing your skills.
Browse courses on Community Involvement
Show steps
  • Identify open source data analytics projects on platforms like GitHub
  • Start contributing by fixing bugs, adding features, or improving documentation
  • Collaborate with other developers and learn from their expertise

Career center

Learners who complete Leveraging Unstructured Data with Cloud Dataproc on Google Cloud em Português Brasileiro will develop knowledge and skills that may be useful to these careers:
Data Engineer
As a Data Engineer, you will be responsible for designing, building, and maintaining the data infrastructure that supports data science and data engineering teams. This course can help you develop the skills you need to build and manage big data infrastructure, which is a critical part of a Data Engineer's job.
Software Engineer
As a Software Engineer, you will play a key role in enabling data science and data engineering by building and maintaining data pipelines, applications, and other infrastructure that enable data to be collected, stored, analyzed, and used to inform decision-making. This course can help you gain the skills necessary to build and manage the big data infrastructure that supports data science and data engineering teams.
Big Data Architect
As a Big Data Architect, you will be responsible for designing and building the big data infrastructure that supports data science and data engineering teams. This course can help you build a foundation in big data processing and machine learning, which are essential skills for Big Data Architects.
Machine Learning Engineer
As a Machine Learning Engineer, you will use your knowledge of machine learning to develop and deploy machine learning models. This course can help you build a foundation in big data processing and machine learning, which are essential skills for Machine Learning Engineers.
Data Scientist
As a Data Scientist, you will use your knowledge of big data and machine learning to extract insights from data and develop predictive models. This course can help you build a foundation in big data processing and machine learning, which are essential skills for Data Scientists.
Data Analyst
As a Data Analyst, you will use your knowledge of data analysis to extract insights from data and develop predictive models. This course can help you build a foundation in big data processing and data analysis, which are essential skills for Data Analysts.
Cloud Architect
As a Cloud Architect, you will be responsible for designing and building cloud-based solutions. This course can help you build a foundation in big data processing and cloud computing, which are essential skills for Cloud Architects.
Database Administrator
As a Database Administrator, you will be responsible for managing and maintaining databases. This course can help you build a foundation in big data processing and database management, which are essential skills for Database Administrators.
Systems Engineer
As a Systems Engineer, you will be responsible for designing, building, and maintaining computer systems. This course can help you build a foundation in big data processing and systems engineering, which are essential skills for Systems Engineers.
Business Analyst
As a Business Analyst, you will use your knowledge of business and data analysis to identify and solve business problems. This course can help you build a foundation in big data processing and data analysis, which are essential skills for Business Analysts.
Project Manager
As a Project Manager, you will be responsible for planning and managing projects. This course can help you build a foundation in big data processing and project management, which are essential skills for Project Managers.
Product Manager
As a Product Manager, you will be responsible for developing and managing products. This course can help you build a foundation in big data processing and product management, which are essential skills for Product Managers.
Technical Writer
As a Technical Writer, you will be responsible for creating technical documentation. This course can help you build a foundation in big data processing and technical writing, which are essential skills for Technical Writers.
Quality Assurance Analyst
As a Quality Assurance Analyst, you will be responsible for testing and ensuring the quality of software. This course can help you build a foundation in big data processing and quality assurance, which are essential skills for Quality Assurance Analysts.
Information Security Analyst
As an Information Security Analyst, you will be responsible for protecting information systems from security threats. This course can help you build a foundation in big data processing and information security, which are essential skills for Information Security Analysts.

Reading list

We've selected ten 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 em Português Brasileiro.
Provides a comprehensive overview of Hadoop, including its architecture, components, and ecosystem. It valuable resource for anyone who wants to learn more about Hadoop and how to use it to process big data. It also provides additional depth and breadth to the course materials.
Provides a comprehensive overview of Spark, including its architecture, components, and ecosystem. It valuable resource for anyone who wants to learn more about Spark and how to use it to process big data. It provides additional depth and breadth to the materials covered during the course.
Provides a comprehensive overview of machine learning with Python. It covers a wide range of topics, including data preprocessing, model training, and evaluation. It valuable resource for anyone who wants to learn more about machine learning with Python, as it can provide additional breadth to the course.
Provides a comprehensive overview of deep learning with Python. It covers a wide range of topics, including neural networks, convolutional neural networks, and recurrent neural networks. It valuable resource for anyone who wants to learn more about deep learning with Python, as it can provide additional breadth to the course.
Provides a comprehensive overview of big data analytics with Java. It covers a wide range of topics, including data storage, processing, and analysis. It valuable resource for anyone who wants to learn more about big data analytics with Java.
Provides a comprehensive overview of data science for business. It covers a wide range of topics, including data collection, analysis, and visualization. It valuable resource for anyone who wants to learn more about data science for business.
Provides a comprehensive overview of data mining for business intelligence. It covers a wide range of topics, including data preprocessing, model training, and evaluation. It valuable resource for anyone who wants to learn more about data mining for business intelligence.
Provides a comprehensive overview of cloud computing. It covers a wide range of topics, including cloud architecture, cloud services, and cloud security. It valuable resource for anyone who wants to learn more about cloud computing. It is helpful for providing useful background knowledge.
Provides a comprehensive overview of data engineering. It covers a wide range of topics, including data storage, processing, and analysis. It valuable resource for anyone who wants to learn more about data engineering. It commonly used as a textbook at academic institutions.

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