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Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console.
Read more
This is a self-paced lab that takes place in the Google Cloud console.
Read more
This is a self-paced lab that takes place in the Google Cloud console.
In this lab you’ll learn how to use an inline Google APIs Explorer template to call the Cloud Dataproc API to create a cluster, run a simple Spark job in the cluster, and update the cluster.
Register for this course and see more details by visiting:
OpenCourser.com/course/1fhmqr/apis
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What's inside
Syllabus
APIs Explorer: Create and Update a Cluster
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Lets learners gain practical experience on the Google Cloud console
Taught by Google Cloud Training, who is recognized for their work in this field
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Save APIs Explorer: Create and Update a Cluster to your list so you can find it easily later:
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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 APIs Explorer: Create and Update a Cluster with these
activities:
Follow a tutorial on the Google Cloud Platform Console
Show steps
Review the basics of the Google Cloud Platform Console to prepare for the course.
Show steps
-
Visit the Google Cloud Platform Console documentation
-
Follow the steps in a tutorial to create a project and enable billing
Create a cluster and run a simple Spark job
Show steps
Practice the skills learned in the course by creating a cluster and running a simple Spark job.
Show steps
-
Create a cluster in the Google Cloud Console
-
Write a simple Spark job
-
Submit the job to the cluster
Create a presentation on the benefits of using Cloud Dataproc
Show steps
Deepen your understanding of Cloud Dataproc by creating a presentation on its benefits.
Show steps
-
Research the benefits of using Cloud Dataproc
-
Create a presentation outline
-
Write the presentation content
Show all three activities
Follow a tutorial on the Google Cloud Platform Console
Show steps
Review the basics of the Google Cloud Platform Console to prepare for the course.
Show steps
Show steps
Show steps
- Visit the Google Cloud Platform Console documentation
- Follow the steps in a tutorial to create a project and enable billing
Create a cluster and run a simple Spark job
Show steps
Practice the skills learned in the course by creating a cluster and running a simple Spark job.
Show steps
Show steps
Show steps
- Create a cluster in the Google Cloud Console
- Write a simple Spark job
- Submit the job to the cluster
Create a presentation on the benefits of using Cloud Dataproc
Show steps
Deepen your understanding of Cloud Dataproc by creating a presentation on its benefits.
Show steps
Show steps
Show steps
- Research the benefits of using Cloud Dataproc
- Create a presentation outline
- Write the presentation content
Show all three activities
Career center
Learners who complete APIs Explorer: Create and Update a Cluster will develop knowledge and skills
that may be useful to these careers:
Project Manager
Project Manager
A Project Manager plans, executes, and closes projects for businesses. They work with stakeholders to define project scope, develop project plans, and manage project resources. This course may be useful for an aspiring Project Manager as it provides an introduction to APIs and the process of creating and updating a cluster. By understanding how to work with data in a cluster environment, you can strengthen your foundation for a career in project management.
Data Scientist
Data Scientist
A Data Scientist uses data to solve business problems. They work with statistics, modeling, and machine learning to analyze data, identify trends and patterns, and make predictions. This course may be useful for an aspiring Data Scientist as it provides an introduction to APIs and the process of creating and updating a cluster. By understanding how to work with data in a cluster environment, you can strengthen your foundation for a career in data science.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and maintains machine learning models. They work with machine learning algorithms and techniques to build and implement predictive models for businesses. This course may be useful for an aspiring Machine Learning Engineer as it provides an introduction to APIs and the process of creating and updating a cluster. By understanding how to work with data in a cluster environment, you can strengthen your foundation for a career in machine learning engineering.
Business Analyst
Business Analyst
A Business Analyst identifies and analyzes business problems and opportunities. They work with stakeholders to gather requirements, develop solutions, and implement changes. This course may be useful for an aspiring Business Analyst as it provides an introduction to APIs and the process of creating and updating a cluster. By understanding how to work with data in a cluster environment, you can strengthen your foundation for a career in business analysis.
Data Architect
Data Architect
A Data Architect designs and manages data architectures for businesses. They work with data models, data integration, and data governance to ensure that data is accessible and usable by all stakeholders. This course may be useful for an aspiring Data Architect as it provides an introduction to APIs and the process of creating and updating a cluster. By understanding how to work with data in a cluster environment, you can strengthen your foundation for a career in data architecture.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications. They work with programming languages and technologies to build and implement software solutions for businesses. This course may be useful for an aspiring Software Engineer as it provides an introduction to APIs and the process of creating and updating a cluster. By understanding how to work with data in a cluster environment, you can strengthen your foundation for a career in software engineering.
Data Analyst
Data Analyst
A Data Analyst consumes and transforms raw data into meaningful, actionable insights. They use statistics, modeling, and machine learning to analyze data, identify trends and patterns, and make predictions. This course may be useful for an aspiring Data Analyst as it provides an introduction to APIs and the process of creating and updating a cluster. By understanding how to work with data in a cluster environment, you can strengthen your foundation for a career in data analysis.
Database Administrator
Database Administrator
A Database Administrator manages and maintains databases for businesses. They work with database technologies and tools to ensure that databases are running smoothly and efficiently. This course may be useful for an aspiring Database Administrator as it provides an introduction to APIs and the process of creating and updating a cluster. By understanding how to work with data in a cluster environment, you can strengthen your foundation for a career in database administration.
Product Manager
Product Manager
A Product Manager defines and manages the development and launch of new products and features. They work with stakeholders to gather requirements, develop product roadmaps, and manage product releases. This course may be useful for an aspiring Product Manager as it provides an introduction to APIs and the process of creating and updating a cluster. By understanding how to work with data in a cluster environment, you can strengthen your foundation for a career in product management.
Data Engineer
Data Engineer
A Data Engineer designs, builds, and maintains data infrastructure. They work with big data technologies to collect, clean, and process data, and ensure that data is accessible and usable by other teams. An aspiring Data Engineer may find this course useful as it provides hands-on experience with creating and updating a cluster, a fundamental skill for managing data infrastructure. By understanding the process of cluster management, you can strengthen your foundation for a career in data engineering.
Cloud Architect
Cloud Architect
A Cloud Architect designs, builds, and manages cloud computing solutions for businesses. They work with cloud technologies to develop and implement cost-effective, scalable, and secure cloud-based solutions. This course may be useful for an aspiring Cloud Architect as it provides hands-on experience with creating and updating a cluster in Google Cloud. By understanding the process of cluster management in a cloud environment, you can strengthen your foundation for a career in cloud architecture.
DevOps Engineer
DevOps Engineer
A DevOps Engineer bridges the gap between development and operations teams. They work with tools and technologies to automate and streamline the software development and deployment process. This course may be useful for an aspiring DevOps Engineer as it provides an introduction to APIs and the process of creating and updating a cluster. By understanding how to work with data in a cluster environment, you can strengthen your foundation for a career in DevOps engineering.
Technical Writer
Technical Writer
A Technical Writer creates and maintains technical documentation for software, products, and services. They work with engineers and other stakeholders to gather information, develop content, and publish documentation. This course may be useful for an aspiring Technical Writer as it provides an introduction to APIs and the process of creating and updating a cluster. By understanding how to work with data in a cluster environment, you can strengthen your foundation for a career in technical writing.
Sales Engineer
Sales Engineer
A Sales Engineer provides technical expertise to customers and helps them to understand and implement solutions. They work with sales teams to identify customer needs, develop technical proposals, and close deals. This course may be useful for an aspiring Sales Engineer as it provides an introduction to APIs and the process of creating and updating a cluster. By understanding how to work with data in a cluster environment, you can strengthen your foundation for a career in sales engineering.
For more career information including salaries, visit:
OpenCourser.com/course/1fhmqr/apis
Reading list
We've selected 11 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
APIs Explorer: Create and Update a Cluster.
The comprehensive guide to Apache Spark, covering its architecture, programming models, and advanced topics. An excellent resource for understanding the fundamentals of Spark.
A comprehensive reference for Hadoop, providing in-depth coverage of its components, configuration, and administration. Useful for understanding the underlying concepts of GCP's Big Data services.
Provides a deep understanding of Hadoop and its ecosystem, including HDFS, MapReduce, and Hive. While it doesn't cover GCP, it offers a solid foundation for understanding the concepts.
Covers advanced machine learning techniques and how to implement them at scale using Python. While it doesn't focus on GCP, it's a valuable resource for understanding machine learning concepts and algorithms.
Provides a practical guide to deep learning using Python, covering neural networks, convolutional neural networks, and recurrent neural networks. While it doesn't focus on GCP, it's valuable for understanding deep learning concepts and techniques.
Offers a practical introduction to big data technologies and techniques, including data storage, processing, and analysis.
Provides a business-oriented perspective on data science, covering data collection, analysis, and visualization.
Provides context and guidance on using AWS for data science, but can also serve as a useful reference for cloud computing concepts and practices.
Save
Provides a comprehensive overview of data visualization principles and techniques.
A gentle introduction to machine learning, covering the basics of supervised and unsupervised learning.
Covers the basics of data science using Python, including data cleaning, manipulation, and visualization.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/1fhmqr/apis
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Effort
1 hour
Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Good to know
Lets learners gain practical experience on the Google Cloud console
Taught by Google Cloud Training, who is recognized for their work in this field
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