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這個入門微學習課程主要說明生成式 AI 的定義和使用方式，以及此 AI 與傳統機器學習方法的差異。本課程也會介紹各項 Google 工具，協助您開發自己的生成式 AI 應用程式。
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What's inside
Syllabus
生成式 AI 簡介
這個入門微學習課程主要說明生成式 AI 的定義和使用方式，以及此 AI 與傳統機器學習方法的差異。本課程也會介紹各項 Google 工具，協助您開發自己的生成式 AI 應用程式。
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
這個入門微學課程主要說明生成式 AI 的定義和使用方式，以及此 AI 與傳統機器學習方法的差異。本課程也會介紹各項 Google 工具，協助您開發自己的生成式 AI 應用程式
Google Cloud Training
Save this course
Save Introduction to Generative AI - 繁體中文 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 - 繁體中文 with these
activities:
Brush up on prerequisite math skills
Show steps
Revisiting prerequisite math concepts will help strengthen your foundation and make the course material easier to grasp.
Show steps
-
Review key concepts from algebra, statistics, and calculus.
-
Practice solving math problems related to the course material.
Follow tutorials on using Google Cloud AI tools
Show steps
Hands-on tutorials will provide you with practical experience using the tools and techniques covered in the course.
Browse courses on
Google Cloud AI Platform
Show steps
-
Identify relevant tutorials from the Google Cloud AI documentation.
-
Set up your development environment and follow the tutorials step-by-step.
-
Experiment with different parameters and scenarios to enhance your understanding.
Discuss generative AI concepts with classmates
Show steps
Engaging in discussions will help you clarify your understanding and gain insights from others.
Browse courses on
Generative AI Applications
Show steps
-
Find a study partner or group who is also taking the course.
-
Schedule regular meetings to discuss course material and share ideas.
-
Take turns presenting on specific topics and leading discussions.
Three other activities
Expand to see all activities and additional details
Show all six activities
Solve coding problems related to generative AI
Show steps
Solving coding problems will reinforce your understanding of the technical aspects of generative AI.
Browse courses on
GANs
Show steps
-
Find online coding challenges or practice platforms related to generative AI.
-
Attempt to solve the problems using the concepts covered in the course.
-
Review your solutions and identify areas for improvement.
Read 'Generative Deep Learning' by David Foster
Show steps
This book provides a comprehensive overview of the theory and practice of generative AI.
View
Generative Deep Learning: Teaching Machines To...
on Amazon
Show steps
-
Read the book thoroughly and take notes on key concepts.
-
Identify sections that are particularly relevant to the course material.
-
Summarize the main ideas and how they connect to what you are learning in the course.
Contribute to an open-source generative AI project
Show steps
Contributing to open-source projects will allow you to learn from others and stay up-to-date with the latest developments in generative AI.
Browse courses on
OpenAI Gym
Show steps
-
Identify an open-source generative AI project that aligns with your interests and skillset.
-
Review the project's documentation and contribute code, bug fixes, or improvements.
-
Engage with the project community through discussions and code reviews.
Brush up on prerequisite math skills
Show steps
Revisiting prerequisite math concepts will help strengthen your foundation and make the course material easier to grasp.
Show steps
Show steps
Show steps
- Review key concepts from algebra, statistics, and calculus.
- Practice solving math problems related to the course material.
Follow tutorials on using Google Cloud AI tools
Show steps
Hands-on tutorials will provide you with practical experience using the tools and techniques covered in the course.
Browse courses on
Google Cloud AI Platform
Show steps
Show steps
Show steps
- Identify relevant tutorials from the Google Cloud AI documentation.
- Set up your development environment and follow the tutorials step-by-step.
- Experiment with different parameters and scenarios to enhance your understanding.
Discuss generative AI concepts with classmates
Show steps
Engaging in discussions will help you clarify your understanding and gain insights from others.
Browse courses on
Generative AI Applications
Show steps
Show steps
Show steps
- Find a study partner or group who is also taking the course.
- Schedule regular meetings to discuss course material and share ideas.
- Take turns presenting on specific topics and leading discussions.
Three other activities
Expand to see all activities and additional details
Show all six activities
Solve coding problems related to generative AI
Show steps
Solving coding problems will reinforce your understanding of the technical aspects of generative AI.
Browse courses on
GANs
Show steps
Show steps
Show steps
- Find online coding challenges or practice platforms related to generative AI.
- Attempt to solve the problems using the concepts covered in the course.
- Review your solutions and identify areas for improvement.
Read 'Generative Deep Learning' by David Foster
Show steps
This book provides a comprehensive overview of the theory and practice of generative AI.
View
Generative Deep Learning: Teaching Machines To...
on Amazon
Show steps
Show steps
Show steps
- Read the book thoroughly and take notes on key concepts.
- Identify sections that are particularly relevant to the course material.
- Summarize the main ideas and how they connect to what you are learning in the course.
Contribute to an open-source generative AI project
Show steps
Contributing to open-source projects will allow you to learn from others and stay up-to-date with the latest developments in generative AI.
Browse courses on
OpenAI Gym
Show steps
Show steps
Show steps
- Identify an open-source generative AI project that aligns with your interests and skillset.
- Review the project's documentation and contribute code, bug fixes, or improvements.
- Engage with the project community through discussions and code reviews.
Career center
Learners who complete Introduction to Generative AI - 繁體中文 will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Generative AI is expected to play a major role in the future of machine learning and artificial intelligence. As a **Machine Learning Engineer**, taking this course will help you gain the skills and knowledge you need to build your career in this important area. This course will provide you with a solid foundation in the use of generative AI models and techniques.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Generative AI is a rapidly growing field, and there is a growing demand for **Artificial Intelligence Engineers** with expertise in this area. This course will provide you with a comprehensive overview of generative AI, and it will teach you how to use Google tools to develop your own generative AI applications.
Data Scientist
Data Scientist
As a **Data Scientist**, your role may involve using generative AI to create synthetic datasets or generating new features for machine learning models. This course on generative AI will provide you with a firm foundation in the use of Google tools in the development of generative AI applications. Take this course to provide yourself with a competitive edge in the job market.
Software Engineer
Software Engineer
Understanding and having working knowledge of generative AI is a boon for a **Software Engineer**. Generative AI is a rapidly growing field, so taking this course may allow you to explore its possibilities and use it to create new and innovative software applications. This course will provide you with a solid foundation for developing your own generative AI applications using Google tools.
Financial Analyst
Financial Analyst
As a **Financial Analyst**, you will analyze financial data to make recommendations to clients. Generative AI can be used to generate new data and to improve the accuracy of models. This course will provide you with a solid foundation in the use of generative AI in financial analysis.
Data Analyst
Data Analyst
As a **Data Analyst**, you will collect, analyze, and interpret data to help organizations make informed decisions. Generative AI can be used to generate new data and features, and to improve the accuracy of machine learning models. This course will provide you with a solid foundation in the use of generative AI in data analysis.
Quantitative Analyst
Quantitative Analyst
As a **Quantitative Analyst**, you will develop and use mathematical and statistical models to analyze data. Generative AI can be used to generate new data and to improve the accuracy of models. This course will provide you with a solid foundation in the use of generative AI in quantitative analysis.
Actuary
Actuary
As an **Actuary**, you will use mathematical and statistical methods to assess risk and uncertainty. Generative AI can be used to generate new data and to improve the accuracy of models. This course will provide you with a solid foundation in the use of generative AI in actuarial science.
Insurance Underwriter
Insurance Underwriter
As an **Insurance Underwriter**, you will assess risk and determine the appropriate insurance premiums. Generative AI can be used to generate new data and to improve the accuracy of models. This course will provide you with a solid foundation in the use of generative AI in insurance underwriting.
Compliance Officer
Compliance Officer
As a **Compliance Officer**, you will ensure that a company is operating in accordance with the law. Generative AI can be used to generate new data and to improve the accuracy of models. This course will provide you with a solid foundation in the use of generative AI in compliance.
Risk Manager
Risk Manager
As a **Risk Manager**, you will identify, assess, and manage risks. Generative AI can be used to generate new data and to improve the accuracy of models. This course will provide you with a solid foundation in the use of generative AI in risk management.
Product Manager
Product Manager
In the role of **Product Manager**, you need to stay abreast of new technologies and trends in order to develop successful products. Generative AI is increasingly being used to create new products and services, so taking this course will provide you with the knowledge you need to stay ahead of the curve.
Business Analyst
Business Analyst
As a **Business Analyst**, you will help organizations to identify and solve problems. Generative AI can be used to generate new ideas and solutions, so taking this course will increase your skillset. This course on generative AI, offered by Google Cloud, may help you develop a foundation in the use of AI tools and technology to solve business problems.
Consultant
Consultant
In the role of **Consultant**, you help clients to solve problems and improve their operations. Generative AI is a powerful tool that can be used to solve a variety of problems, so taking this course will give you the knowledge and skills you need to succeed in this field. This course may be particularly helpful for those who wish to specialize in technology consulting.
Marketing Manager
Marketing Manager
When you are a **Marketing Manager**, you will often need to use technology to carry out your day to day functions. Any exposure to AI and machine learning technology can increase your chances of promotion. This is a field that is constantly advancing, so you need to stay informed. Taking this course on generative AI may help you develop any potential gaps in knowledge that you have.
For more career information including salaries, visit:
OpenCourser.com/course/v9rkmy/introduction
Reading list
We've selected nine 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 - 繁體中文.
一本統計學習的經典教科書，全面介紹了統計學習的原理、技術和應用。對於想要深入了解生成式人工智能的統計基礎，這是一本非常好的選擇。
一本專門介紹機器學習的數學基礎的書籍，深入探討了線性代數、微積分、概率論等數學知識在機器學習中的應用。對於想要深入了解生成式人工智能的數學基礎，這是一本非常好的選擇。
一本模式識別和機器學習的經典教科書，全面介紹了模式識別和機器學習的原理、技術和應用。對於想要深入了解生成式人工智能的數學基礎，這是一本非常好的選擇。
Save
一本專門介紹生成對抗網絡（GAN）的書籍，深入探討了 GAN 的原理、技術和應用。對於想要了解生成式人工智能在圖像生成、文本生成等領域的應用，這是一本非常好的選擇。
Save
一本計算機視覺的經典教科書，全面介紹了計算機視覺的原理、技術和應用。對於想要了解生成式人工智能在計算機視覺領域的應用，這是一本非常好的選擇。
一本強化學習的經典教科書，全面介紹了強化學習的原理、技術和應用。對於想要了解生成式人工智能在強化學習領域的應用，這是一本非常好的選擇。
一本語音和語言處理的經典教科書，全面介紹了語音和語言處理的原理、技術和應用。對於想要了解生成式人工智能在自然語言處理領域的應用，這是一本非常好的選擇。
一本經典的深度學習教科書，全面介紹了深度學習的原理、技術和應用。對於想要深入了解深度學習技術的讀者來說，這是一本非常好的選擇。
一本簡明扼要的機器學習入門書籍，適合沒有機器學習背景的讀者。對於想要快速了解生成式人工智能的基礎知識，這是一本非常好的選擇。
For more information about how these books relate to this course, visit:
OpenCourser.com/course/v9rkmy/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
中文
Transcript
English
Good to know
這個入門微學課程主要說明生成式 AI 的定義和使用方式，以及此 AI 與傳統機器學習方法的差異。本課程也會介紹各項 Google 工具，協助您開發自己的生成式 AI 應用程式
Google Cloud Training
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