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Google Cloud Training
Take Udacity's free Cloud Introduction to Generative AI Course by Google and learn what Generative AI is, Generative AI is, how it's used, and how it differs from traditional machine learning methods.
Register for this course and see more details by visiting:
OpenCourser.com/course/mgorfx/introduction
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What's inside
Syllabus
This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores Generative AI, a rapidly evolving field at the intersection of machine learning and artificial intelligence
Taught by Google Cloud Training, a recognized leader in the field of cloud computing and artificial intelligence
Develops a foundational understanding of generative AI techniques and their applications
Introduces key concepts of generative AI, such as deep learning models, neural networks, and natural language processing
Provides real-world examples and case studies to illustrate the practical uses of generative AI
Save this course
Save Introduction to Generative AI with Google Cloud 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 Introduction to Generative AI with Google Cloud with these
activities:
Review machine learning fundamentals
Show steps
Refresh your knowledge of basic machine learning concepts and techniques, such as supervised and unsupervised learning, to establish a strong foundation for understanding generative AI.
Browse courses on
Machine Learning
Show steps
-
Review key concepts of machine learning, including supervised learning, unsupervised learning, and model evaluation.
-
Go through practice problems and exercises to reinforce your understanding.
Follow tutorials on generative AI basics
Show steps
Enhance your understanding of generative AI by following online tutorials that provide step-by-step guidance on building and training generative models.
Browse courses on
Generative AI
Show steps
-
Find reputable tutorials that cover the basics of generative AI techniques like GANs and VAEs.
-
Set up the necessary software and environment for running the tutorials.
-
Follow the instructions in the tutorials to create and train your own generative models, using sample datasets provided or gathering your own.
-
Evaluate the results of your models and troubleshoot any issues encountered.
Experiment with generative AI models
Show steps
Gain hands-on experience with generative AI models by implementing them from scratch or using existing libraries.
Browse courses on
Generative AI
Show steps
-
Choose a specific generative AI technique, such as GANs or VAEs, to focus on.
-
Find sample datasets or gather your own data that is suitable for the chosen technique.
-
Implement or use existing libraries to create and train your own generative models.
-
Evaluate the performance of your models using appropriate metrics and make adjustments as needed.
Three other activities
Expand to see all activities and additional details
Show all six activities
Contribute to GitHub project
Show steps
Contribute code or documentation to open source Generative AI projects to solidify understanding and gain feedback
Show steps
-
Identify a generative AI project on GitHub that aligns with your interests and skills
-
Review the project's codebase and documentation to understand its structure and goals
-
Identify an area where you can make a meaningful contribution, such as bug fixes, feature enhancements, or documentation improvements
-
Collaborate with the project maintainers to discuss your proposal and get feedback
-
Complete your contribution and submit a pull request
Write summaries on key generative AI research papers
Show steps
Deepen your understanding of generative AI by summarizing and critically analyzing recent research papers in the field.
Browse courses on
Generative AI
Show steps
-
Identify recent and influential research papers on generative AI.
-
Read and understand the papers thoroughly, focusing on the key concepts, methods, and results.
-
Summarize the main points of the papers in your own words, highlighting their contributions and significance.
-
Optionally, provide a critical analysis of the papers, discussing their strengths, limitations, and potential implications.
Participate in generative AI challenges or hackathons
Show steps
Challenge yourself and test your skills by participating in generative AI competitions or hackathons, where you can apply your knowledge and creativity to solve real-world problems.
Browse courses on
Generative AI
Show steps
-
Find and register for generative AI competitions or hackathons that align with your interests and skill level.
-
Form a team or work individually to develop and submit your solutions.
-
Attend the competition or hackathon and present your work to judges or peers.
-
Reflect on your experience and identify areas for improvement.
Review machine learning fundamentals
Show steps
Refresh your knowledge of basic machine learning concepts and techniques, such as supervised and unsupervised learning, to establish a strong foundation for understanding generative AI.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Review key concepts of machine learning, including supervised learning, unsupervised learning, and model evaluation.
- Go through practice problems and exercises to reinforce your understanding.
Follow tutorials on generative AI basics
Show steps
Enhance your understanding of generative AI by following online tutorials that provide step-by-step guidance on building and training generative models.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
- Find reputable tutorials that cover the basics of generative AI techniques like GANs and VAEs.
- Set up the necessary software and environment for running the tutorials.
- Follow the instructions in the tutorials to create and train your own generative models, using sample datasets provided or gathering your own.
- Evaluate the results of your models and troubleshoot any issues encountered.
Experiment with generative AI models
Show steps
Gain hands-on experience with generative AI models by implementing them from scratch or using existing libraries.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
- Choose a specific generative AI technique, such as GANs or VAEs, to focus on.
- Find sample datasets or gather your own data that is suitable for the chosen technique.
- Implement or use existing libraries to create and train your own generative models.
- Evaluate the performance of your models using appropriate metrics and make adjustments as needed.
Three other activities
Expand to see all activities and additional details
Show all six activities
Contribute to GitHub project
Show steps
Contribute code or documentation to open source Generative AI projects to solidify understanding and gain feedback
Show steps
Show steps
Show steps
- Identify a generative AI project on GitHub that aligns with your interests and skills
- Review the project's codebase and documentation to understand its structure and goals
- Identify an area where you can make a meaningful contribution, such as bug fixes, feature enhancements, or documentation improvements
- Collaborate with the project maintainers to discuss your proposal and get feedback
- Complete your contribution and submit a pull request
Write summaries on key generative AI research papers
Show steps
Deepen your understanding of generative AI by summarizing and critically analyzing recent research papers in the field.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
- Identify recent and influential research papers on generative AI.
- Read and understand the papers thoroughly, focusing on the key concepts, methods, and results.
- Summarize the main points of the papers in your own words, highlighting their contributions and significance.
- Optionally, provide a critical analysis of the papers, discussing their strengths, limitations, and potential implications.
Participate in generative AI challenges or hackathons
Show steps
Challenge yourself and test your skills by participating in generative AI competitions or hackathons, where you can apply your knowledge and creativity to solve real-world problems.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
- Find and register for generative AI competitions or hackathons that align with your interests and skill level.
- Form a team or work individually to develop and submit your solutions.
- Attend the competition or hackathon and present your work to judges or peers.
- Reflect on your experience and identify areas for improvement.
Career center
Learners who complete Introduction to Generative AI with Google Cloud will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists are responsible for collecting, cleaning, and analyzing data to extract insights and make predictions. This course in Generative AI will help you build a foundation in the field. You will learn how to use Generative AI to generate new data, which can be used to train machine learning models or to create new products and services.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for designing, building, and deploying machine learning models. This course in Generative AI will help you build a foundation in the field. You will learn how to use Generative AI to generate new data, which can be used to train machine learning models or to create new products and services.
Software Engineer
Software Engineer
Software Engineers are responsible for designing, developing, and maintaining software applications. This course in Generative AI will help you build a foundation in the field. You will learn how to use Generative AI to generate new code, which can be used to create new products and services.
Data Analyst
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data to extract insights and make predictions. This course in Generative AI may be useful for Data Analysts who want to learn how to use Generative AI to generate new data, which can be used to train machine learning models or to create new products and services.
Product Manager
Product Manager
Product Managers are responsible for managing the development and launch of new products and services. This course in Generative AI may be useful for Product Managers who want to learn how to use Generative AI to generate new ideas for products and services.
Financial Analyst
Financial Analyst
Financial Analysts are responsible for analyzing financial data and making investment recommendations. This course in Generative AI may be useful for Financial Analysts who want to learn how to use Generative AI to generate new investment ideas.
Operations Manager
Operations Manager
Operations Managers are responsible for managing business operations and improving efficiency. This course in Generative AI may be useful for Operations Managers who want to learn how to use Generative AI to generate new ideas for improving operations.
Consultant
Consultant
Consultants are responsible for providing advice and guidance to businesses and organizations. This course in Generative AI may be useful for Consultants who want to learn how to use Generative AI to generate new ideas for consulting services.
Entrepreneur
Entrepreneur
Entrepreneurs are responsible for starting and running their own businesses. This course in Generative AI may be useful for Entrepreneurs who want to learn how to use Generative AI to generate new ideas for products and services.
Human Resources Manager
Human Resources Manager
Human Resources Managers are responsible for managing employee relations and developing HR policies. This course in Generative AI may be useful for Human Resources Managers who want to learn how to use Generative AI to generate new ideas for employee development.
Teacher
Teacher
Teachers are responsible for educating students in a variety of subjects. This course in Generative AI may be useful for Teachers who want to learn how to use Generative AI to generate new lesson plans and teaching materials.
Marketing Manager
Marketing Manager
Marketing Managers are responsible for developing and executing marketing campaigns. This course in Generative AI may be useful for Marketing Managers who want to learn how to use Generative AI to generate new marketing content.
Project Manager
Project Manager
Project Managers are responsible for planning, executing, and closing projects. This course in Generative AI may be useful for Project Managers who want to learn how to use Generative AI to generate new ideas for project management.
Sales Manager
Sales Manager
Sales Managers are responsible for managing sales teams and developing sales strategies. This course in Generative AI may be useful for Sales Managers who want to learn how to use Generative AI to generate new leads and close more deals.
Business Analyst
Business Analyst
Business Analysts are responsible for analyzing business processes and identifying opportunities for improvement. This course in Generative AI may be useful for Business Analysts who want to learn how to use Generative AI to generate new ideas for products and services.
For more career information including salaries, visit:
OpenCourser.com/course/mgorfx/introduction
Reading list
We've selected seven 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
Introduction to Generative AI with Google Cloud.
Teaches the fundamentals of deep learning using the fastai library. It great resource for anyone who wants to learn how to build and train generative AI models.
Provides a comprehensive introduction to deep learning using Python. It great resource for anyone who wants to learn more about the theory and practice of deep learning.
Provides a comprehensive overview of computer vision. It great resource for anyone who wants to learn more about the theory and practice of computer vision.
Save
Provides a comprehensive overview of machine learning for the humanities. It great resource for anyone who wants to learn more about the theory and practice of machine learning in the context of the humanities.
Provides a comprehensive overview of data science for business. It great resource for anyone who wants to learn more about the theory and practice of data science in the context of business.
Save
Provides a comprehensive overview of artificial intelligence for medicine. It great resource for anyone who wants to learn more about the theory and practice of AI in the context of medicine.
Provides a comprehensive overview of the ethical implications of AI. It great resource for anyone who wants to learn more about the ethical challenges and opportunities posed by AI.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/mgorfx/introduction
Share
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Effort
45 minutes
Via
Udacity
Instructor
Google Cloud Training
Language
English
Good to know
Explores Generative AI, a rapidly evolving field at the intersection of machine learning and artificial intelligence
Taught by Google Cloud Training, a recognized leader in the field of cloud computing and artificial intelligence
Develops a foundational understanding of generative AI techniques and their applications
Introduces key concepts of generative AI, such as deep learning models, neural networks, and natural language processing
Provides real-world examples and case studies to illustrate the practical uses of generative AI
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