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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 will simulate a real-time real world data set from a historical data set. This simulated data set will be processed from a set of text files using Python and Google Cloud DataFlow, and the resulting simulated real-time data will be stored in Google BigQuery.
Register for this course and see more details by visiting:
OpenCourser.com/course/hwgto1/processing
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Provides hands-on labs for a more interactive learning experience
Builds a solid foundation in data processing techniques using Google Cloud technologies
Teaches skills and knowledge relevant to industry standards in data processing
Course instructors are recognized experts in Google Cloud
Requires prerequisite knowledge or experience in cloud computing and data processing
Uses specific versions of software and tools that may require further updates or knowledge
Save this course
Save Processing Data with Google Cloud Dataflow 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 Processing Data with Google Cloud Dataflow with these
activities:
Review Big Data Concepts
Show steps
Refresh your understanding of Big Data concepts to enhance your learning in this course.
Browse courses on
Big Data
Show steps
-
Review lecture notes or textbooks from previous courses
-
Read articles or watch videos on Big Data fundamentals
Practice Data Cleaning Techniques
Show steps
Sharpen your data cleaning skills before starting the course to improve your data handling abilities.
Browse courses on
Data Cleaning
Show steps
-
Find a dataset that requires cleaning
-
Apply data cleaning techniques to remove errors and inconsistencies
Create Practice DataSets
Show steps
Practice creating simulated dataSets to develop a stronger understanding of data processing.
Show steps
-
Install necessary Python libraries and Google Cloud SDK
-
Create a new Python script and import the libraries
-
Generate sample data from scratch or use an existing dataset
-
Write code to simulate real-time data using Python and Google Cloud DataFlow
-
Store the simulated data in Google BigQuery
Five other activities
Expand to see all activities and additional details
Show all eight activities
Google Cloud DataFlow Tutorial
Show steps
Follow a guided tutorial to strengthen your understanding of Google Cloud DataFlow.
Show steps
-
Visit the official Google Cloud DataFlow documentation
-
Select a suitable tutorial for your skill level
-
Follow the instructions and complete the tutorial
-
Experiment with different code examples provided in the tutorial
Join a Study Group
Show steps
Collaborate with peers to discuss course concepts and reinforce your understanding.
Show steps
-
Reach out to classmates or online forums to find interested individuals
-
Establish regular meeting times and a communication channel
-
Take turns presenting and discussing different course topics
-
Work together on practice problems and assignments
Data Analytics Resources Compilation
Show steps
Gather valuable resources to support your learning beyond the course.
Show steps
-
Create a document or online repository
-
Collect and organize relevant articles, tutorials, and datasets
-
Categorize and tag the resources for easy access
-
Share your compilation with others
Attend a Google Cloud DataFlow Workshop
Show steps
Participate in a workshop to enhance your practical skills in Google Cloud DataFlow.
Show steps
-
Search for upcoming Google Cloud DataFlow workshops
-
Register for a workshop that aligns with your schedule
-
Attend the workshop and actively participate in the exercises
-
Network with other participants and experts
Participate in a Data Analytics Competition
Show steps
Challenge yourself by participating in a competition to apply your skills and gain recognition.
Show steps
-
Identify a relevant data analytics competition
-
Form a team or work individually on the competition
-
Analyze the provided data and develop a solution
-
Submit your solution and compete for recognition
Review Big Data Concepts
Show steps
Refresh your understanding of Big Data concepts to enhance your learning in this course.
Browse courses on
Big Data
Show steps
Show steps
Show steps
- Review lecture notes or textbooks from previous courses
- Read articles or watch videos on Big Data fundamentals
Practice Data Cleaning Techniques
Show steps
Sharpen your data cleaning skills before starting the course to improve your data handling abilities.
Browse courses on
Data Cleaning
Show steps
Show steps
Show steps
- Find a dataset that requires cleaning
- Apply data cleaning techniques to remove errors and inconsistencies
Create Practice DataSets
Show steps
Practice creating simulated dataSets to develop a stronger understanding of data processing.
Show steps
Show steps
Show steps
- Install necessary Python libraries and Google Cloud SDK
- Create a new Python script and import the libraries
- Generate sample data from scratch or use an existing dataset
- Write code to simulate real-time data using Python and Google Cloud DataFlow
- Store the simulated data in Google BigQuery
Five other activities
Expand to see all activities and additional details
Show all eight activities
Google Cloud DataFlow Tutorial
Show steps
Follow a guided tutorial to strengthen your understanding of Google Cloud DataFlow.
Show steps
Show steps
Show steps
- Visit the official Google Cloud DataFlow documentation
- Select a suitable tutorial for your skill level
- Follow the instructions and complete the tutorial
- Experiment with different code examples provided in the tutorial
Join a Study Group
Show steps
Collaborate with peers to discuss course concepts and reinforce your understanding.
Show steps
Show steps
Show steps
- Reach out to classmates or online forums to find interested individuals
- Establish regular meeting times and a communication channel
- Take turns presenting and discussing different course topics
- Work together on practice problems and assignments
Data Analytics Resources Compilation
Show steps
Gather valuable resources to support your learning beyond the course.
Show steps
Show steps
Show steps
- Create a document or online repository
- Collect and organize relevant articles, tutorials, and datasets
- Categorize and tag the resources for easy access
- Share your compilation with others
Attend a Google Cloud DataFlow Workshop
Show steps
Participate in a workshop to enhance your practical skills in Google Cloud DataFlow.
Show steps
Show steps
Show steps
- Search for upcoming Google Cloud DataFlow workshops
- Register for a workshop that aligns with your schedule
- Attend the workshop and actively participate in the exercises
- Network with other participants and experts
Participate in a Data Analytics Competition
Show steps
Challenge yourself by participating in a competition to apply your skills and gain recognition.
Show steps
Show steps
Show steps
- Identify a relevant data analytics competition
- Form a team or work individually on the competition
- Analyze the provided data and develop a solution
- Submit your solution and compete for recognition
Career center
Learners who complete Processing Data with Google Cloud Dataflow will develop knowledge and skills
that may be useful to these careers:
Data Engineer
Data Engineer
A Data Engineer ensures that large datasets are readily available to Data Analysts and Scientists for both querying and analysis. Taking the Processing Data with Google Cloud Dataflow course would help build a foundation for this career, as it teaches you how to process streaming data using Google's cloud-based services. This course may also be of interest to those who plan to become Data Engineers because it provides hands-on experience in developing and deploying data pipelines.
Data Analyst
Data Analyst
A Data Analyst uses their expertise in statistics and data mining to extract insights from large datasets. This course may be useful for aspiring Data Analysts because it provides hands-on experience using Google Cloud's services to process and analyze large amounts of data.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer develops and deploys machine learning models that analyze and interpret data. This course may be useful for aspiring Machine Learning Engineers, as it provides hands-on experience using Google's cloud-based services to process and analyze large amounts of data, which is essential for developing effective machine learning models.
Software Engineer
Software Engineer
A Software Engineer designs, develops, tests, and maintains software systems. This course may be useful for aspiring Software Engineers, as it provides hands-on experience using Google's cloud-based services to process and analyze large amounts of data. This experience can be valuable for Software Engineers who work on projects that involve big data or real-time data analysis.
Data Scientist
Data Scientist
A Data Scientist uses statistical and machine learning techniques to uncover insights from data. This course may be useful for aspiring Data Scientists because it provides hands-on experience using Google Cloud's services to process and analyze large amounts of data. This experience can be valuable for Data Scientists who work on projects that involve big data or real-time data analysis.
Cloud Architect
Cloud Architect
A Cloud Architect designs, builds, and manages cloud-based systems. This course may be useful for aspiring Cloud Architects, as it provides hands-on experience using Google's cloud-based services to process and analyze large amounts of data. This experience can be valuable for Cloud Architects who work on projects that involve big data or real-time data analysis.
Big Data Engineer
Big Data Engineer
A Big Data Engineer designs and manages systems for processing and analyzing large datasets. This course may be useful for aspiring Big Data Engineers, as it provides hands-on experience using Google's cloud-based services to process and analyze large amounts of data. This experience can be valuable for Big Data Engineers who work on projects that involve big data or real-time data analysis.
Information Security Analyst
Information Security Analyst
An Information Security Analyst protects computer systems and networks from unauthorized access, use, disclosure, disruption, modification, or destruction. This course may be useful for aspiring Information Security Analysts, as it provides hands-on experience using Google's cloud-based services to process and analyze large amounts of data. This experience can be valuable for Information Security Analysts who work on projects that involve big data or real-time data analysis.
Database Administrator
Database Administrator
A Database Administrator manages and maintains databases. This course may be useful for aspiring Database Administrators, as it provides hands-on experience using Google's cloud-based services to process and analyze large amounts of data. This experience can be valuable for Database Administrators who work on projects that involve big data or real-time data analysis.
System Administrator
System Administrator
A System Administrator manages and maintains computer systems. This course may be useful for aspiring System Administrators, as it provides hands-on experience using Google's cloud-based services to process and analyze large amounts of data. This experience can be valuable for System Administrators who work on projects that involve big data or real-time data analysis.
Data Warehouse Engineer
Data Warehouse Engineer
A Data Warehouse Engineer designs and manages data warehouses. This course may be useful for aspiring Data Warehouse Engineers, as it provides hands-on experience using Google's cloud-based services to process and analyze large amounts of data. This experience can be valuable for Data Warehouse Engineers who work on projects that involve big data or real-time data analysis.
Business Intelligence Analyst
Business Intelligence Analyst
A Business Intelligence Analyst uses data to help businesses make better decisions. This course may be useful for aspiring Business Intelligence Analysts, as it provides hands-on experience using Google's cloud-based services to process and analyze large amounts of data. This experience can be valuable for Business Intelligence Analysts who work on projects that involve big data or real-time data analysis.
IT Manager
IT Manager
An IT Manager plans and directs the implementation and maintenance of computer systems and networks. This course may be useful for aspiring IT Managers, as it provides hands-on experience using Google's cloud-based services to process and analyze large amounts of data. This experience can be valuable for IT Managers who work on projects that involve big data or real-time data analysis.
Web Developer
Web Developer
A Web Developer designs and develops websites. This course may be useful for aspiring Web Developers, as it provides hands-on experience using Google's cloud-based services to process and analyze large amounts of data. This experience can be valuable for Web Developers who work on projects that involve big data or real-time data analysis.
Network Administrator
Network Administrator
A Network Administrator manages and maintains computer networks. This course may be useful for aspiring Network Administrators, as it provides hands-on experience using Google's cloud-based services to process and analyze large amounts of data. This experience can be valuable for Network Administrators who work on projects that involve big data or real-time data analysis.
For more career information including salaries, visit:
OpenCourser.com/course/hwgto1/processing
Reading list
We've selected six 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
Processing Data with Google Cloud Dataflow.
Save
Comprehensive guide to designing and building data-intensive applications.
Comprehensive guide to data science with Python. It covers everything from the basics of data science to advanced topics such as machine learning and deep learning. It valuable resource for anyone who wants to learn more about data science.
Comprehensive guide to building real-time data pipelines using Apache Beam and Google Cloud Platform.
Comprehensive guide to machine learning with Python. It covers everything from the basics of machine learning to advanced topics such as deep learning. It valuable resource for anyone who wants to learn more about machine learning.
Comprehensive guide to deep learning with Python. It covers everything from the basics of deep learning to advanced topics such as convolutional neural networks and recurrent neural networks. It valuable resource for anyone who wants to learn more about deep learning.
Comprehensive guide to Python for data analysis. It covers everything from the basics of Python to advanced topics such as data manipulation and machine learning. It valuable resource for anyone who wants to learn more about Python for data analysis.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/hwgto1/processing
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Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Good to know
Provides hands-on labs for a more interactive learning experience
Builds a solid foundation in data processing techniques using Google Cloud technologies
Teaches skills and knowledge relevant to industry standards in data processing
Course instructors are recognized experts in Google Cloud
Requires prerequisite knowledge or experience in cloud computing and data processing
Uses specific versions of software and tools that may require further updates or knowledge
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