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この入門レベルのマイクロラーニング コースでは、ジェネレーティブ AI の概要、利用方法、従来の機械学習の手法との違いについて説明します。独自のジェネレーティブ AI アプリを作成する際に利用できる Google ツールも紹介します。
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OpenCourser.com/course/eyzyf1/introduction
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What's inside
Syllabus
ジェネレーティブ AI の概要
この入門レベルのマイクロラーニング コースでは、ジェネレーティブ AI の概要、利用方法、従来の機械学習の手法との違いについて説明します。独自のジェネレーティブ AI アプリを作成する際に利用できる Google ツールも紹介します。
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
This course assists learners in creating their own generative AI apps
By teaching the fundamentals of generative AI, this course provides a strong foundation for beginners
This is an introductory level course
Save this course
Save Introduction to Generative AI - 日本語版 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 - 日本語版 with these
activities:
Review introductory AI concepts
Show steps
Refreshes the student on fundamental AI concepts in preparation for the course
Browse courses on
AI Fundamentals
Show steps
-
Review online resources, such as articles, videos, and tutorials, covering introductory AI concepts.
-
Attend online workshops or webinars on AI basics.
Seek mentorship from experts in generative AI
Show steps
Provides access to valuable guidance and networking opportunities
Show steps
-
Identify professionals in the field of generative AI who could serve as mentors.
-
Contact them via email or LinkedIn, expressing your interest in mentorship and outlining your goals.
-
Arrange regular meetings or communication channels to receive guidance and support.
Follow online tutorials on generative AI tools
Show steps
Provides hands-on experience in using generative AI tools from Google
Show steps
-
Identify online tutorials that cover the use of generative AI tools offered by Google.
-
Follow the tutorials step-by-step, experimenting with the tools and exploring their capabilities.
-
Apply the tools to create your own generative AI projects.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Solve AI-related coding problems
Show steps
Provides hands-on practice in applying AI techniques and algorithms
Show steps
-
Find online coding platforms or websites that offer AI-related coding challenges.
-
Choose problems that align with the topics covered in the course.
-
Attempt to solve the problems independently, and refer to course materials or online resources for assistance when needed.
-
Review solutions and explanations to reinforce understanding.
Join a study group to discuss generative AI topics
Show steps
Facilitates collaboration and knowledge sharing among students
Show steps
-
Find or create a study group with peers taking the same course.
-
Schedule regular group meetings to discuss course concepts, share resources, and work on problems together.
Compile resources on generative AI applications
Show steps
Helps students stay organized and easily access relevant information
Show steps
-
Gather resources such as articles, white papers, tutorials, and code samples related to generative AI applications.
-
Organize the resources into a central location, such as a shared folder or a collaborative document.
-
Periodically review and update the compilation to include the latest developments in the field.
Build a simple AI application
Show steps
Allows the student to apply AI concepts and techniques in a practical context
Show steps
-
Identify a specific problem or task that can be solved using AI.
-
Choose appropriate AI techniques and algorithms for the task.
-
Implement the AI solution using a programming language.
-
Test and evaluate the performance of the application.
-
Share the application with classmates or other online communities for feedback.
Contribute to open-source generative AI projects
Show steps
Provides practical experience and exposure to real-world generative AI applications
Show steps
-
Identify open-source generative AI projects that align with your interests.
-
Review the project documentation and contribute to discussions on issue trackers or forums.
-
Submit bug reports or feature requests to improve the project.
-
Optionally, contribute code or documentation to the project.
Review introductory AI concepts
Show steps
Refreshes the student on fundamental AI concepts in preparation for the course
Browse courses on
AI Fundamentals
Show steps
Show steps
Show steps
- Review online resources, such as articles, videos, and tutorials, covering introductory AI concepts.
- Attend online workshops or webinars on AI basics.
Seek mentorship from experts in generative AI
Show steps
Provides access to valuable guidance and networking opportunities
Show steps
Show steps
Show steps
- Identify professionals in the field of generative AI who could serve as mentors.
- Contact them via email or LinkedIn, expressing your interest in mentorship and outlining your goals.
- Arrange regular meetings or communication channels to receive guidance and support.
Follow online tutorials on generative AI tools
Show steps
Provides hands-on experience in using generative AI tools from Google
Show steps
Show steps
Show steps
- Identify online tutorials that cover the use of generative AI tools offered by Google.
- Follow the tutorials step-by-step, experimenting with the tools and exploring their capabilities.
- Apply the tools to create your own generative AI projects.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Solve AI-related coding problems
Show steps
Provides hands-on practice in applying AI techniques and algorithms
Show steps
Show steps
Show steps
- Find online coding platforms or websites that offer AI-related coding challenges.
- Choose problems that align with the topics covered in the course.
- Attempt to solve the problems independently, and refer to course materials or online resources for assistance when needed.
- Review solutions and explanations to reinforce understanding.
Join a study group to discuss generative AI topics
Show steps
Facilitates collaboration and knowledge sharing among students
Show steps
Show steps
Show steps
- Find or create a study group with peers taking the same course.
- Schedule regular group meetings to discuss course concepts, share resources, and work on problems together.
Compile resources on generative AI applications
Show steps
Helps students stay organized and easily access relevant information
Show steps
Show steps
Show steps
- Gather resources such as articles, white papers, tutorials, and code samples related to generative AI applications.
- Organize the resources into a central location, such as a shared folder or a collaborative document.
- Periodically review and update the compilation to include the latest developments in the field.
Build a simple AI application
Show steps
Allows the student to apply AI concepts and techniques in a practical context
Show steps
Show steps
Show steps
- Identify a specific problem or task that can be solved using AI.
- Choose appropriate AI techniques and algorithms for the task.
- Implement the AI solution using a programming language.
- Test and evaluate the performance of the application.
- Share the application with classmates or other online communities for feedback.
Contribute to open-source generative AI projects
Show steps
Provides practical experience and exposure to real-world generative AI applications
Show steps
Show steps
Show steps
- Identify open-source generative AI projects that align with your interests.
- Review the project documentation and contribute to discussions on issue trackers or forums.
- Submit bug reports or feature requests to improve the project.
- Optionally, contribute code or documentation to the project.
Career center
Learners who complete Introduction to Generative AI - 日本語版 will develop knowledge and skills
that may be useful to these careers:
Machine Learning Scientist
Machine Learning Scientist
A Machine Learning Scientist designs and builds machine learning models that solve business problems. This course may be helpful to a Machine Learning Scientist by demonstrating how generative AI can be a useful tool in developing and deploying machine learning models.
AI Engineer
AI Engineer
An AI Engineer applies their expertise in machine learning and other areas of data science to build AI applications and services. This course may be helpful to an AI Engineer by providing a basic understanding of how generative AI can be employed in the development of AI powered products and services.
Data Scientist
Data Scientist
A Data Scientist uses their knowledge of data, statistics, and machine learning to solve business problems and gain valuable insights from data. This course may be helpful to a Data Scientist by providing an introduction to generative AI, and how to use it in the context of data analysis and machine learning.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications. This course may be helpful to a Software Engineer who wants to learn how to use generative AI in the software development process.
Product Manager
Product Manager
A Product Manager is responsible for the development and launch of new products and features. This course may be helpful to a Product Manager by providing an understanding of how generative AI can be used to create new and innovative products and features.
Data Engineer
Data Engineer
A Data Engineer designs and builds data pipelines that collect, store, and process data. This course may be helpful to a Data Engineer who wants to learn how to use generative AI to improve data pipelines.
Business Analyst
Business Analyst
A Business Analyst works with stakeholders to define and analyze business needs. This course may be helpful to a Business Analyst who wants to learn how to use generative AI to identify and analyze business needs.
Data Analyst
Data Analyst
A Data Analyst transforms raw data into meaningful insights. This course may be helpful to a Data Analyst by providing an introduction to generative AI, and how to use it to improve data analysis.
Project Manager
Project Manager
A Project Manager plans, executes, and closes projects. This course may be helpful to a Project Manager who wants to learn how to use generative AI to improve project planning and execution.
IT Manager
IT Manager
An IT Manager plans and executes the IT strategy of an organization. This course may be helpful to an IT Manager who wants to learn how to use generative AI to improve the IT infrastructure.
Technical Writer
Technical Writer
A Technical Writer creates documentation for software and other technical products. This course may be helpful to a Technical Writer who wants to learn how to use generative AI to improve the quality of documentation.
UX Designer
UX Designer
A UX Designer creates user interfaces for websites and applications. This course may be helpful to a UX Designer who wants to learn how to use generative AI to improve the user experience of websites and applications.
Teacher
Teacher
A Teacher educates students in a variety of subjects. This course may be helpful to a Teacher who wants to learn how to use generative AI to improve the quality of education they provide to students.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical models to analyze financial data. This course may be helpful to a Quantitative Analyst who wants to learn how to use generative AI to improve financial analysis.
Consultant
Consultant
A Consultant provides advice and expertise to clients on a variety of business issues. This course may be helpful to a Consultant who wants to learn how to use generative AI to improve the quality of advice and expertise they provide to clients.
For more career information including salaries, visit:
OpenCourser.com/course/eyzyf1/introduction
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
Introduction to Generative AI - 日本語版.
Save
このコースでは、ジェネレーティブ AI の構築に使用されるディープラーニングの原理と手法について学びます。
Save
このコースでは、強化学習の基礎とアルゴリズムについて学びます。
Save
このコースでは、確率と統計の基本概念について学びます。
このコースでは、線形代数の基本概念について学びます。
このコースでは、微積分の基本概念について学びます。
この実践的なガイドでは、Python を使用してディープラーニングモデルを構築する方法について学ぶことができます。
For more information about how these books relate to this course, visit:
OpenCourser.com/course/eyzyf1/introduction
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Effort
1 week of study, 6-8 hours
Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
日本語
Transcript
English
Good to know
This course assists learners in creating their own generative AI apps
By teaching the fundamentals of generative AI, this course provides a strong foundation for beginners
This is an introductory level course
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