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Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console.
In this lab you spin up a virtual machine, configure its security, access it remotely, and then carry out the steps of an ingest-transform-and-publish data pipeline manually. This lab is part of a series of labs on processing scientific data.
Register for this course and see more details by visiting:
OpenCourser.com/course/74hr1z/rent
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What's inside
Syllabus
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This course will require learners to have a foundation in data science and cloud computing
You will need basic knowledge of Linux commands, data structures, and algorithms
Provides hands-on experience in using the Google Cloud Platform to process scientific data
Taught by Google Cloud Training, which has a strong reputation in the industry
Covers the fundamentals of data processing in a cloud environment
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Reviews summary
Practical google cloud vm lab
According to students, this course offers a largely positive and highly practical experience for setting up virtual machines on Google Cloud and executing manual data processing pipelines. Learners consistently praise the hands-on activities and find the instructions generally clear, making it valuable for acquiring real-world skills. While the lab environment proves effective, some reviewers note that certain documentation and console screenshots may be slightly outdated, causing minor navigation challenges. Students widely agree the course provides a solid foundational understanding of Google Compute Engine and basic data workflows. However, opinions diverge regarding its suitability for absolute beginners, with some finding it challenging without prior cloud knowledge, suggesting it is best for those with some technical background.
Provides a strong base in GCP VMs and manual data processing workflows.
"It's a good foundational lab for anyone getting into cloud data processing."
"Solid lab. It teaches you the basics of setting up a VM on GCP and processing data."
"Good introduction to GCE for data processing. The 'ingest-transform-publish' flow is well demonstrated."
The step-by-step guidance is largely well-explained and easy to follow.
"The steps for spinning up the VM and configuring security were clear, though I had some prior experience with GCP."
"I especially appreciated the detailed instructions for remote access."
"The instructions were crystal clear for the most part, and I successfully set up my VM and processed the data..."
Offers valuable, direct experience with Google Cloud VMs and data processing.
"A very practical lab that directly applies to real-world data processing."
"Excellent hands-on introduction to Google Cloud VMs and basic data pipeline concepts."
"Phenomenal practical experience. ...This lab is a gem for anyone looking to get hands-on with GCP compute..."
Some console interface screenshots or documentation may be outdated.
"I found some parts of the documentation slightly outdated, especially with the Google Cloud console interface changes."
"This made a few steps confusing. The core VM setup and data processing worked fine, but be prepared for minor discrepancies..."
May be challenging for absolute beginners without prior cloud knowledge.
"I struggled with this lab. As a complete beginner, I found it very difficult to follow."
"The pace was too fast, and it assumes too much prior knowledge of cloud concepts."
"Ended up spending a lot of time debugging things that weren't clearly explained. Not for absolute novices."
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 Rent-a-VM to Process Earthquake Data with these
activities:
Connect with experts in data processing
Show steps
Seek guidance and insights from experienced professionals in the field of data processing
Browse courses on
Data Processing
Show steps
-
Attend industry events and meetups
-
Reach out to professionals on LinkedIn and other professional networking platforms
-
Join online communities and forums dedicated to data processing
Form a study group with fellow learners
Show steps
Enhance understanding through collaboration and discussions with other learners
Show steps
-
Identify fellow learners through online forums or discussion boards
-
Establish a regular meeting schedule and format
-
Share notes, discuss course concepts, and work on assignments together
Practice SSH and command-line operations
Show steps
Strengthen foundational skills in using SSH and command-line tools to navigate and manage virtual machines
Browse courses on
SSH
Show steps
-
Review SSH and command-line syntax
-
Connect to a virtual machine using SSH
-
Perform basic file and directory operations using command-line tools
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice creating virtual machines
Show steps
Review essential skills for creating and managing virtual machines to ensure they're ready for the lab
Browse courses on
Virtual Machines
Show steps
-
Review documentation and tutorials on virtual machine creation
-
Set up a cloud account and create a virtual machine in the console or using the command line
-
Configure network and security settings for the virtual machine
Explore Google Cloud security best practices
Show steps
Enhance understanding of security configurations for Google Cloud platforms used in the lab
Browse courses on
Google Cloud Security
Show steps
-
Review Google Cloud security documentation and tutorials
-
Explore security recommendations and best practices for different Google Cloud services
-
Identify potential security vulnerabilities and mitigation strategies
Develop a data processing script
Show steps
Apply knowledge gained in the lab by creating a custom script to process and transform data
Browse courses on
Data Processing
Show steps
-
Document the script and its functionality
-
Design a data processing pipeline based on the lab exercise
-
Implement the pipeline using a programming language of your choice
-
Test and refine the script to ensure accurate data processing
Contribute to a scientific data processing project
Show steps
Gain practical experience and contribute to the broader scientific community by participating in an open-source data processing project
Show steps
-
Identify an open-source project related to scientific data processing
-
Review the project's codebase and documentation
-
Propose a feature or improvement to the project
-
Implement your contribution and submit a pull request
Connect with experts in data processing
Show steps
Seek guidance and insights from experienced professionals in the field of data processing
Browse courses on
Data Processing
Show steps
Show steps
Show steps
- Attend industry events and meetups
- Reach out to professionals on LinkedIn and other professional networking platforms
- Join online communities and forums dedicated to data processing
Form a study group with fellow learners
Show steps
Enhance understanding through collaboration and discussions with other learners
Show steps
Show steps
Show steps
- Identify fellow learners through online forums or discussion boards
- Establish a regular meeting schedule and format
- Share notes, discuss course concepts, and work on assignments together
Practice SSH and command-line operations
Show steps
Strengthen foundational skills in using SSH and command-line tools to navigate and manage virtual machines
Browse courses on
SSH
Show steps
Show steps
Show steps
- Review SSH and command-line syntax
- Connect to a virtual machine using SSH
- Perform basic file and directory operations using command-line tools
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice creating virtual machines
Show steps
Review essential skills for creating and managing virtual machines to ensure they're ready for the lab
Browse courses on
Virtual Machines
Show steps
Show steps
Show steps
- Review documentation and tutorials on virtual machine creation
- Set up a cloud account and create a virtual machine in the console or using the command line
- Configure network and security settings for the virtual machine
Explore Google Cloud security best practices
Show steps
Enhance understanding of security configurations for Google Cloud platforms used in the lab
Browse courses on
Google Cloud Security
Show steps
Show steps
Show steps
- Review Google Cloud security documentation and tutorials
- Explore security recommendations and best practices for different Google Cloud services
- Identify potential security vulnerabilities and mitigation strategies
Develop a data processing script
Show steps
Apply knowledge gained in the lab by creating a custom script to process and transform data
Browse courses on
Data Processing
Show steps
Show steps
Show steps
- Document the script and its functionality
- Design a data processing pipeline based on the lab exercise
- Implement the pipeline using a programming language of your choice
- Test and refine the script to ensure accurate data processing
Contribute to a scientific data processing project
Show steps
Gain practical experience and contribute to the broader scientific community by participating in an open-source data processing project
Show steps
Show steps
Show steps
- Identify an open-source project related to scientific data processing
- Review the project's codebase and documentation
- Propose a feature or improvement to the project
- Implement your contribution and submit a pull request
Career center
Learners who complete Rent-a-VM to Process Earthquake Data will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist collects raw data and uses it to develop machine learning models or other analytical solutions. This course may be useful for this role because it provides hands-on experience in spinning up virtual machines and processing earthquake data.
Data Engineer
Data Engineer
A Data Engineer designs and builds scalable data pipelines to process and transform large volumes of data. This course may be helpful for this role because it provides hands-on experience in setting up and managing virtual machines and processing earthquake data.
DevOps Engineer
DevOps Engineer
A DevOps Engineer automates and streamlines the software development and deployment process. This course may be useful for this role because it provides hands-on experience in setting up and managing virtual machines and processing earthquake data.
Cloud Architect
Cloud Architect
A Cloud Architect designs and manages cloud computing solutions. This course may be useful for this role because it provides hands-on experience in setting up and managing virtual machines and processing earthquake data.
Systems Administrator
Systems Administrator
A Systems Administrator manages and maintains computer systems and networks. This course may be useful for this role because it provides hands-on experience in setting up and managing virtual machines and processing earthquake data.
Security Analyst
Security Analyst
A Security Analyst protects computer systems and networks from unauthorized access and attacks. This course may be useful for this role because it provides hands-on experience in setting up and managing virtual machines and processing earthquake data.
Network Engineer
Network Engineer
A Network Engineer designs and manages computer networks. This course may be useful for this role because it provides hands-on experience in setting up and managing virtual machines and processing earthquake data.
Database Administrator
Database Administrator
A Database Administrator manages and maintains databases. This course may be useful for this role because it provides hands-on experience in setting up and managing virtual machines and processing earthquake data.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and tests software applications. This course may be useful for this role because it provides hands-on experience in setting up and managing virtual machines and processing earthquake data.
Data Analyst
Data Analyst
A Data Analyst analyzes data to identify trends and patterns. This course may be useful for this role because it provides hands-on experience in setting up and managing virtual machines and processing earthquake data.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer develops and deploys machine learning models. This course may be useful for this role because it provides hands-on experience in setting up and managing virtual machines and processing earthquake data.
AI Engineer
AI Engineer
An AI Engineer develops and deploys artificial intelligence models. This course may be useful for this role because it provides hands-on experience in setting up and managing virtual machines and processing earthquake data.
Cloud Security Engineer
Cloud Security Engineer
A Cloud Security Engineer protects cloud computing environments from unauthorized access and attacks. This course may be useful for this role because it provides hands-on experience in setting up and managing virtual machines and processing earthquake data.
Data Visualization Engineer
Data Visualization Engineer
A Data Visualization Engineer designs and develops data visualizations. This course may be useful for this role because it provides hands-on experience in setting up and managing virtual machines and processing earthquake data.
Geophysicist
Geophysicist
A Geophysicist studies the physical properties of the Earth. This course may be useful for this role because it provides hands-on experience in setting up and managing virtual machines and processing earthquake data.
For more career information including salaries, visit:
OpenCourser.com/course/74hr1z/rent
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
Rent-a-VM to Process Earthquake Data.
Practical guide to machine learning in Python. It covers topics such as data preprocessing, model selection, and evaluation. This book valuable resource for anyone who wants to learn how to use machine learning in Python.
Comprehensive guide to data analysis in Python. It covers topics such as data cleaning, data manipulation, and data visualization. This book valuable resource for anyone who wants to learn how to use Python for data analysis.
Practical guide to Python for data science. It covers topics such as data wrangling, data analysis, and machine learning. This book valuable resource for anyone who wants to learn how to use Python for data science.
Comprehensive guide to data science for business. It covers topics such as data collection, data analysis, and data visualization.
Gentle introduction to machine learning. It covers topics such as supervised learning, unsupervised learning, and reinforcement learning.
Comprehensive guide to deep learning in Python. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks.
Practical guide to TensorFlow for deep learning. It covers topics such as building and training neural networks, and using TensorFlow for natural language processing and computer vision.
Comprehensive guide to natural language processing in Python. It covers topics such as tokenization, stemming, lemmatization, and parsing.
Comprehensive guide to speech and language processing. It covers topics such as speech recognition, speech synthesis, and natural language understanding.
Save
Comprehensive guide to computer vision. It covers topics such as image processing, feature extraction, and object recognition.
Save
Comprehensive guide to deep learning. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/74hr1z/rent
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