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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 develop, deploy, and run a TFX pipeline on Google Cloud Vertex Pipelines.
Register for this course and see more details by visiting:
OpenCourser.com/course/nymjcu/tfx
What's inside
Syllabus
TFX on Google Cloud Vertex Pipelines
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches TFX on Google Cloud Vertex Pipelines, which is used in industry
Develops experience in using the Google Cloud console
Offers self-paced learning, which is convenient for learners
Taught by Google Cloud Training, who are recognized for their work in cloud computing
Hands-on labs and interactive materials provide practical experience
May require prior knowledge of TFX and Google Cloud Vertex Pipelines
Save this course
Save TFX on Google Cloud Vertex Pipelines 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 TFX on Google Cloud Vertex Pipelines with these
activities:
Find a mentor
Show steps
Finding a mentor can provide you with guidance and support throughout your learning journey.
Show steps
-
Identify potential mentors who have experience in the field
-
Reach out to potential mentors and request their guidance
Review linear algebra
Show steps
Reviewing linear algebra will help you refresh your knowledge on the fundamentals of the subject, which will be essential for success in this course.
Browse courses on
Matrix Operations
Show steps
-
Review linear algebra concepts such as vectors, matrices, and transformations
-
Practice solving linear algebra problems
Join a study group
Show steps
Joining a study group will provide you with a supportive environment to learn with other students and get help with difficult concepts.
Show steps
-
Find a study group or create your own
-
Meet regularly to discuss course material and work on assignments
Three other activities
Expand to see all activities and additional details
Show all six activities
Write a blog post about a machine learning topic
Show steps
Writing a blog post about a machine learning topic will help you solidify your understanding of the subject and share your knowledge with others.
Show steps
-
Choose a machine learning topic that you are interested in
-
Research the topic and gather information
-
Write a blog post that is clear, concise, and informative
Build a simple machine learning model
Show steps
Building a simple machine learning model will help you apply the concepts you learn in this course to a practical project.
Show steps
-
Choose a dataset and define the problem you want to solve
-
Preprocess the data and prepare it for training
-
Train and evaluate a machine learning model
-
Deploy the model and make predictions
Participate in a machine learning competition
Show steps
Participating in a machine learning competition will challenge you to apply your skills to a real-world problem and compete with other students.
Show steps
-
Find a machine learning competition that interests you
-
Prepare for the competition by practicing your skills
-
Submit your solution to the competition
Find a mentor
Show steps
Finding a mentor can provide you with guidance and support throughout your learning journey.
Show steps
Show steps
Show steps
- Identify potential mentors who have experience in the field
- Reach out to potential mentors and request their guidance
Review linear algebra
Show steps
Reviewing linear algebra will help you refresh your knowledge on the fundamentals of the subject, which will be essential for success in this course.
Browse courses on
Matrix Operations
Show steps
Show steps
Show steps
- Review linear algebra concepts such as vectors, matrices, and transformations
- Practice solving linear algebra problems
Join a study group
Show steps
Joining a study group will provide you with a supportive environment to learn with other students and get help with difficult concepts.
Show steps
Show steps
Show steps
- Find a study group or create your own
- Meet regularly to discuss course material and work on assignments
Three other activities
Expand to see all activities and additional details
Show all six activities
Write a blog post about a machine learning topic
Show steps
Writing a blog post about a machine learning topic will help you solidify your understanding of the subject and share your knowledge with others.
Show steps
Show steps
Show steps
- Choose a machine learning topic that you are interested in
- Research the topic and gather information
- Write a blog post that is clear, concise, and informative
Build a simple machine learning model
Show steps
Building a simple machine learning model will help you apply the concepts you learn in this course to a practical project.
Show steps
Show steps
Show steps
- Choose a dataset and define the problem you want to solve
- Preprocess the data and prepare it for training
- Train and evaluate a machine learning model
- Deploy the model and make predictions
Participate in a machine learning competition
Show steps
Participating in a machine learning competition will challenge you to apply your skills to a real-world problem and compete with other students.
Show steps
Show steps
Show steps
- Find a machine learning competition that interests you
- Prepare for the competition by practicing your skills
- Submit your solution to the competition
Career center
Learners who complete TFX on Google Cloud Vertex Pipelines will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer is responsible for developing and deploying machine learning models. Machine Learning Engineers work with data scientists and engineers to build and maintain machine learning systems. This course may be useful for someone who wants to become a Machine Learning Engineer because it provides a foundation in machine learning and data engineering.
Machine Learning Researcher
Machine Learning Researcher
A Machine Learning Researcher is responsible for developing new machine learning algorithms and techniques. Machine Learning Researchers work with a variety of mathematical and statistical techniques to develop new ways to solve problems with machine learning. This course may be useful for someone who wants to become a Machine Learning Researcher because it provides a foundation in machine learning and data analysis.
Data Scientist
Data Scientist
A Data Scientist is responsible for using data to solve business problems. Data Scientists use a variety of machine learning and statistical techniques to analyze data and make predictions. This course may be useful for someone who wants to become a Data Scientist because it provides a foundation in data science and machine learning.
Data Architect
Data Architect
A Data Architect is responsible for designing and managing data systems. Data Architects work with a variety of data technologies to build and maintain data systems that meet the needs of the organization. This course may be useful for someone who wants to become a Data Architect because it provides a foundation in data management and machine learning.
Software Engineer
Software Engineer
A Software Engineer is responsible for designing, developing, and maintaining software applications. Software Engineers work with a variety of programming languages and technologies to build and maintain software systems. This course may be useful for someone who wants to become a Software Engineer because it provides a foundation in software development and machine learning.
Data Analyst
Data Analyst
A Data Analyst is responsible for collecting, cleaning, and analyzing data to identify trends and patterns. Data Analysts use their findings to make recommendations and solve business problems. This course may be useful for someone who wants to become a Data Analyst because it provides a foundation in data analysis and machine learning.
Risk Analyst
Risk Analyst
A Risk Analyst is responsible for identifying and assessing risks. Risk Analysts work with a variety of data and analytical techniques to develop risk management strategies. This course may be useful for someone who wants to become a Risk Analyst because it provides a foundation in data analysis and machine learning.
Product Manager
Product Manager
A Product Manager is responsible for managing the development and launch of new products. Product Managers work with a variety of stakeholders to gather requirements and define the product vision. This course may be useful for someone who wants to become a Product Manager because it provides a foundation in data analysis and machine learning.
Data Engineer
Data Engineer
A Data Engineer is responsible for designing, building, and maintaining data pipelines. Data Engineers work with data analysts and scientists to ensure that data is available and accessible for analysis. This course may be useful for someone who wants to become a Data Engineer because it provides a foundation in data engineering and machine learning.
DevOps Engineer
DevOps Engineer
A DevOps Engineer is responsible for bridging the gap between development and operations teams. DevOps Engineers work with a variety of tools and technologies to automate and streamline the software development process. This course may be useful for someone who wants to become a DevOps Engineer because it provides a foundation in software development and machine learning.
Cloud Engineer
Cloud Engineer
A Cloud Engineer is responsible for designing, building, and maintaining cloud computing systems. Cloud Engineers work with a variety of cloud computing technologies to build and maintain cloud-based applications and services. This course may be useful for someone who wants to become a Cloud Engineer because it provides a foundation in cloud computing and machine learning.
Quant Analyst
Quant Analyst
A Quant Analyst is responsible for using quantitative methods to analyze financial data. Quant Analysts work with a variety of statistical and machine learning techniques to develop trading models. This course may be useful for someone who wants to become a Quant Analyst because it provides a foundation in data analysis and machine learning.
Data Visualization Engineer
Data Visualization Engineer
A Data Visualization Engineer is responsible for designing and developing data visualizations. Data Visualization Engineers work with a variety of data visualization tools and technologies to create visualizations that communicate data insights. This course may be useful for someone who wants to become a Data Visualization Engineer because it provides a foundation in data analysis and machine learning.
Business Analyst
Business Analyst
A Business Analyst is responsible for analyzing business processes and identifying areas for improvement. Business Analysts work with a variety of stakeholders to gather requirements and develop solutions to business problems. This course may be useful for someone who wants to become a Business Analyst because it provides a foundation in data analysis and machine learning.
Statistician
Statistician
A Statistician is responsible for collecting, analyzing, and interpreting data. Statisticians work with a variety of statistical techniques to develop models and make predictions. This course may be useful for someone who wants to become a Statistician because it provides a foundation in data analysis and machine learning.
For more career information including salaries, visit:
OpenCourser.com/course/nymjcu/tfx
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
TFX on Google Cloud Vertex Pipelines.
Provides a comprehensive introduction to deep learning, including its history, algorithms, and applications. It good resource for those who want to gain a deep understanding of deep learning and its potential.
Provides a comprehensive introduction to Hadoop, a distributed computing framework for big data processing. It covers the core concepts of Hadoop, as well as how to use it to build data pipelines and perform complex data analysis tasks.
Save
Covers the fundamental concepts and techniques for designing and building data-intensive applications. It provides valuable background knowledge for understanding the challenges and solutions involved in managing large-scale data and building reliable ML pipelines.
Provides a comprehensive overview of the data science process, including data acquisition, exploration, modeling, and visualization. It good resource for those who want to gain a broad understanding of the field and learn how to apply data science techniques in practice.
Provides a comprehensive overview of the data science process, with a focus on business applications. It covers a wide range of topics, including data collection, exploration, modeling, and visualization.
Great resource for Swift developers who want to learn how to use TensorFlow. It provides a gentle introduction to TensorFlow, as well as more advanced topics such as TFX.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/nymjcu/tfx
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Effort
1.5 hours
Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Good to know
Teaches TFX on Google Cloud Vertex Pipelines, which is used in industry
Develops experience in using the Google Cloud console
Offers self-paced learning, which is convenient for learners
Taught by Google Cloud Training, who are recognized for their work in cloud computing
Hands-on labs and interactive materials provide practical experience
May require prior knowledge of TFX and Google Cloud Vertex Pipelines
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