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このコースは、大規模言語モデル（LLM）とは何か、どのようなユースケースで活用できるのか、プロンプト調整で LLM のパフォーマンスを高めるにはどうすればよいかについて学習する、入門レベルのマイクロ ラーニング コースです。ジェネレーティブ AI アプリを自分で作成するのに役立つ Google ツールについても紹介します。
Register for this course and see more details by visiting:
OpenCourser.com/course/1c053a/introduction
What's inside
Syllabus
大規模言語モデルの概要
このモジュールでは、大規模言語モデル（LLM）とは何か、どのようなユースケースで活用できるのか、プロンプト調整で LLM のパフォーマンスを高めるにはどうすればよいかについて学習します。ジェネレーティブ AI アプリを自分で作成するのに役立つ Google ツールについても紹介します。
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
対象者は、大規模言語モデル（LLM）とそのユースケースについての基本的な理解を深めたい方です。
ジェネレーティブ AI アプリを作成するのに役立つ Google ツールも紹介するため、実践的なスキルを身に付けることができます。
入門レベルのマイクロラーニングコースであるため、LLM の基本を短時間で効率的に学ぶことができます。
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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 Large Language Models - 日本語版 with these
activities:
Review Basics of Natural Language Processing
Show steps
Review the foundational concepts of Natural Language Processing to strengthen your understanding of the course materials.
Browse courses on
Natural Language Processing
Show steps
-
Read articles or blog posts on NLP basics.
-
Review lecture notes or textbooks on NLP fundamentals.
Review LLM Concepts
Show steps
Refresh your understanding of the fundamentals of LLM to enhance your engagement in this course.
Browse courses on
Large Language Models
Show steps
-
Read an overview of LLM concepts.
-
Watch a video tutorial on LLM.
-
Complete a practice exercise on LLM.
Gather Resources on LLMs
Show steps
Compile a collection of useful resources and tools related to LLM to support your learning throughout the course.
Show steps
-
Search for online articles and tutorials on LLM.
-
Subscribe to LLM-related newsletters.
-
Follow experts in the field on social media.
-
Explore online repositories of LLM models.
12 other activities
Expand to see all activities and additional details
Show all 15 activities
Join a Study Group for Course Discussions
Show steps
Engage with fellow learners in a study group to discuss course topics, share insights, and enhance your understanding.
Show steps
-
Find or create a study group with other students enrolled in the course.
-
Meet regularly to discuss lecture materials, assignments, and projects.
Participate in LLM Study Group
Show steps
Engage with fellow students in a study group to discuss LLM concepts and share insights, fostering a supportive and collaborative learning environment.
Show steps
-
Find or start a study group with other students.
-
Schedule regular meetings to discuss course materials.
-
Take turns presenting topics and leading discussions.
Practice Prompt Writing Exercises
Show steps
Improve your prompt writing skills through dedicated practice exercises.
Show steps
-
Find online exercises or challenges that focus on prompt writing.
-
Write prompts for different tasks and scenarios.
Explore Hugging Face Models
Show steps
Review Hugging Face's models and resources to enhance your understanding of LLM capabilities.
Browse courses on
Hugging Face
Show steps
-
Visit the Hugging Face website
-
Browse the model hub
-
Choose a model
-
Use the model in a notebook
Apply Prompt Engineering Techniques
Show steps
Engage in practical exercises to master prompt engineering techniques, enabling you to effectively communicate with and obtain optimal results from LLM.
Browse courses on
Prompt Engineering
Show steps
-
Practice writing prompts using specific formats.
-
Experiment with different prompting styles.
-
Analyze the impact of different prompts on LLM outputs.
Follow Tutorials on Prompt Engineering
Show steps
Enhance your understanding of prompt engineering techniques to improve the performance of LLMs.
Browse courses on
Prompt Engineering
Show steps
-
Follow online tutorials on prompt engineering best practices.
-
Experiment with different prompt formats and variations.
Fine-tune LLM Prompts
Show steps
Practice refining prompts to enhance LLM outputs and achieve desired results.
Browse courses on
Prompt Engineering
Show steps
-
Choose a prompt
-
Identify areas for improvement
-
Experiment with variations
-
Analyze results
-
Refine the prompt
Build an LLM App
Show steps
Apply your LLM knowledge to create a functional app that leverages LLM capabilities.
Show steps
-
Identify a problem
-
Design the app
-
Develop the app
-
Test the app
-
Deploy the app
Develop a Generative AI Application
Show steps
Apply your knowledge of LLM to design and build a functional generative AI application, demonstrating your proficiency in practical implementation.
Browse courses on
Generative AI
Show steps
-
Identify a problem or opportunity suitable for a generative AI solution.
-
Design the architecture of the application.
-
Implement the application using Google tools.
-
Test and refine the application.
Write a Blog Post on LLM Applications
Show steps
Solidify your understanding of LLM applications by creating a blog post that explores their practical uses.
Show steps
-
Research different use cases of LLMs.
-
Choose a specific application and write about its benefits and limitations.
Develop a Prototype LLM Application
Show steps
Apply your knowledge by creating a prototype of an LLM-powered application, showcasing your understanding of their capabilities.
Show steps
-
Identify a problem or opportunity that can be addressed with an LLM.
-
Design and develop a prototype that leverages the capabilities of an LLM.
-
Test and refine your prototype.
Contribute to an Open-Source LLM Project
Show steps
Gain practical experience and contribute to the broader LLM community by participating in open-source projects.
Browse courses on
Open Source
Show steps
-
Identify open-source LLM projects that align with your interests.
-
Review the project documentation and codebase.
-
Identify areas where you can contribute, such as bug fixes, feature enhancements, or documentation improvements.
-
Submit your contributions to the project.
Review Basics of Natural Language Processing
Show steps
Review the foundational concepts of Natural Language Processing to strengthen your understanding of the course materials.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Read articles or blog posts on NLP basics.
- Review lecture notes or textbooks on NLP fundamentals.
Review LLM Concepts
Show steps
Refresh your understanding of the fundamentals of LLM to enhance your engagement in this course.
Browse courses on
Large Language Models
Show steps
Show steps
Show steps
- Read an overview of LLM concepts.
- Watch a video tutorial on LLM.
- Complete a practice exercise on LLM.
Gather Resources on LLMs
Show steps
Compile a collection of useful resources and tools related to LLM to support your learning throughout the course.
Show steps
Show steps
Show steps
- Search for online articles and tutorials on LLM.
- Subscribe to LLM-related newsletters.
- Follow experts in the field on social media.
- Explore online repositories of LLM models.
12 other activities
Expand to see all activities and additional details
Show all 15 activities
Join a Study Group for Course Discussions
Show steps
Engage with fellow learners in a study group to discuss course topics, share insights, and enhance your understanding.
Show steps
Show steps
Show steps
- Find or create a study group with other students enrolled in the course.
- Meet regularly to discuss lecture materials, assignments, and projects.
Participate in LLM Study Group
Show steps
Engage with fellow students in a study group to discuss LLM concepts and share insights, fostering a supportive and collaborative learning environment.
Show steps
Show steps
Show steps
- Find or start a study group with other students.
- Schedule regular meetings to discuss course materials.
- Take turns presenting topics and leading discussions.
Practice Prompt Writing Exercises
Show steps
Improve your prompt writing skills through dedicated practice exercises.
Show steps
Show steps
Show steps
- Find online exercises or challenges that focus on prompt writing.
- Write prompts for different tasks and scenarios.
Explore Hugging Face Models
Show steps
Review Hugging Face's models and resources to enhance your understanding of LLM capabilities.
Browse courses on
Hugging Face
Show steps
Show steps
Show steps
- Visit the Hugging Face website
- Browse the model hub
- Choose a model
- Use the model in a notebook
Apply Prompt Engineering Techniques
Show steps
Engage in practical exercises to master prompt engineering techniques, enabling you to effectively communicate with and obtain optimal results from LLM.
Browse courses on
Prompt Engineering
Show steps
Show steps
Show steps
- Practice writing prompts using specific formats.
- Experiment with different prompting styles.
- Analyze the impact of different prompts on LLM outputs.
Follow Tutorials on Prompt Engineering
Show steps
Enhance your understanding of prompt engineering techniques to improve the performance of LLMs.
Browse courses on
Prompt Engineering
Show steps
Show steps
Show steps
- Follow online tutorials on prompt engineering best practices.
- Experiment with different prompt formats and variations.
Fine-tune LLM Prompts
Show steps
Practice refining prompts to enhance LLM outputs and achieve desired results.
Browse courses on
Prompt Engineering
Show steps
Show steps
Show steps
- Choose a prompt
- Identify areas for improvement
- Experiment with variations
- Analyze results
- Refine the prompt
Build an LLM App
Show steps
Apply your LLM knowledge to create a functional app that leverages LLM capabilities.
Show steps
Show steps
Show steps
- Identify a problem
- Design the app
- Develop the app
- Test the app
- Deploy the app
Develop a Generative AI Application
Show steps
Apply your knowledge of LLM to design and build a functional generative AI application, demonstrating your proficiency in practical implementation.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
- Identify a problem or opportunity suitable for a generative AI solution.
- Design the architecture of the application.
- Implement the application using Google tools.
- Test and refine the application.
Write a Blog Post on LLM Applications
Show steps
Solidify your understanding of LLM applications by creating a blog post that explores their practical uses.
Show steps
Show steps
Show steps
- Research different use cases of LLMs.
- Choose a specific application and write about its benefits and limitations.
Develop a Prototype LLM Application
Show steps
Apply your knowledge by creating a prototype of an LLM-powered application, showcasing your understanding of their capabilities.
Show steps
Show steps
Show steps
- Identify a problem or opportunity that can be addressed with an LLM.
- Design and develop a prototype that leverages the capabilities of an LLM.
- Test and refine your prototype.
Contribute to an Open-Source LLM Project
Show steps
Gain practical experience and contribute to the broader LLM community by participating in open-source projects.
Browse courses on
Open Source
Show steps
Show steps
Show steps
- Identify open-source LLM projects that align with your interests.
- Review the project documentation and codebase.
- Identify areas where you can contribute, such as bug fixes, feature enhancements, or documentation improvements.
- Submit your contributions to the project.
Career center
Learners who complete Introduction to Large Language Models - 日本語版 will develop knowledge and skills
that may be useful to these careers:
Natural Language Processing Engineer
Natural Language Processing Engineer
A Natural Language Processing Engineer is responsible for designing, developing, and maintaining natural language processing systems. This course may be useful in helping to build a foundation in the fundamentals of LLMs, which are a critical component of many NLP systems. Additionally, the knowledge gained from this course may be helpful in understanding how to prompt and interact with LLMs to achieve desired outcomes.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer is responsible for designing, developing, and maintaining machine learning models. This course may be useful in helping to build a foundation in the fundamentals of LLMs, which are a critical component of many machine learning models. Additionally, the knowledge gained from this course may be helpful in understanding how to prompt and interact with LLMs to achieve desired outcomes.
Copywriter
Copywriter
A Copywriter is responsible for writing persuasive and engaging copy for marketing and advertising campaigns. This course may be useful in helping to build a foundation in the fundamentals of LLMs, which can be used to generate copy, optimize for conversions, and create impactful messaging.
Data Scientist
Data Scientist
A Data Scientist is responsible for collecting, analyzing, and interpreting data. This course may be useful in helping to build a foundation in the fundamentals of LLMs, which are becoming increasingly important in the field of data science. LLMs can be used to automate tasks such as data cleaning and feature engineering, which can free up data scientists to focus on more strategic tasks.
Content Writer
Content Writer
A Content Writer is responsible for creating written content for websites, blogs, and other marketing materials. This course may be useful in helping to build a foundation in the fundamentals of LLMs, which can be used to generate content, optimize for SEO, and create engaging copy.
Technical Writer
Technical Writer
A Technical Writer is responsible for creating technical documentation, such as user manuals and white papers. This course may be useful in helping to build a foundation in the fundamentals of LLMs, which can be used to generate documentation, optimize for clarity, and create effective communication materials.
Software Developer
Software Developer
A Software Developer is responsible for designing, developing, and maintaining software applications. This course may be useful in helping to build a foundation in the fundamentals of LLMs, which are becoming increasingly important in the field of software development. LLMs can be used to automate tasks such as code generation and debugging, which can free up software developers to focus on more strategic tasks.
Academic Researcher
Academic Researcher
An Academic Researcher is responsible for conducting research and publishing findings in academic journals. This course may be useful in helping to build a foundation in the fundamentals of LLMs, which can be used to generate research ideas, optimize for impact, and create groundbreaking discoveries.
UX Writer
UX Writer
A UX Writer is responsible for writing clear and concise text for user interfaces and other user-facing content. This course may be useful in helping to build a foundation in the fundamentals of LLMs, which can be used to generate UX copy, optimize for usability, and create delightful user experiences.
AI Engineer
AI Engineer
An AI Engineer is responsible for designing, developing, and maintaining artificial intelligence systems. This course may be useful in helping to build a foundation in the fundamentals of LLMs, which are a critical component of many AI systems. Additionally, the knowledge gained from this course may be helpful in understanding how to prompt and interact with LLMs to achieve desired outcomes.
Grant Writer
Grant Writer
A Grant Writer is responsible for writing grant proposals to secure funding for non-profit organizations and other entities. This course may be useful in helping to build a foundation in the fundamentals of LLMs, which can be used to generate grant proposals, optimize for impact, and create compelling narratives.
Marketing Manager
Marketing Manager
A Marketing Manager is responsible for developing and executing marketing campaigns. This course may be useful in helping to build a foundation in the fundamentals of LLMs, which can be used to generate marketing content, target audiences, and measure campaign performance.
Journalist
Journalist
A Journalist is responsible for gathering, analyzing, and reporting on news and current events. This course may be useful in helping to build a foundation in the fundamentals of LLMs, which can be used to generate news articles, optimize for engagement, and create informative and compelling content.
Business Analyst
Business Analyst
A Business Analyst is responsible for analyzing business processes and identifying opportunities for improvement. This course may be useful in helping to build a foundation in the fundamentals of LLMs, which can be used to generate business insights, optimize for efficiency, and create innovative solutions.
Product Manager
Product Manager
A Product Manager is responsible for managing the development and launch of new products. This course may be useful in helping to build a foundation in the fundamentals of LLMs, which can be used to gather customer feedback, generate product ideas, and create marketing content.
For more career information including salaries, visit:
OpenCourser.com/course/1c053a/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 Large Language Models - 日本語版.
自然言語処理の包括的な教科書です。LLM の開発と応用に関連するトピックを幅広くカバーしています。
Save
チューリングの画期的な論文「コンピューティング・マシナリーと知能」を注釈付きで解説しています。LLM の基礎となった概念を理解するのに役立ちます。
ディープラーニングの基礎から実践までを網羅した教科書。大規模言語モデルの開発やトレーニングに興味がある受講者にとって役立ちます。
Save
ディープラーニングの包括的な教科書です。LLM の基礎となる概念と手法について理解を深めることができます。
機械学習の基礎を体系的に解説した教科書。大規模言語モデルの開発やトレーニングを理解するための前提知識として役立ちます。
TensorFlowを使用したディープラーニングの包括的なガイドブック。大規模言語モデルのトレーニングやデプロイメントに興味がある受講者にとって役立ちます。
人工知能の包括的な教科書。大規模言語モデルの開発や応用を理解するための前提知識として役立ちます。
For more information about how these books relate to this course, visit:
OpenCourser.com/course/1c053a/introduction
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Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
日本語
Transcript
English
Good to know
対象者は、大規模言語モデル（LLM）とそのユースケースについての基本的な理解を深めたい方です。
ジェネレーティブ AI アプリを作成するのに役立つ Google ツールも紹介するため、実践的なスキルを身に付けることができます。
入門レベルのマイクロラーニングコースであるため、LLM の基本を短時間で効率的に学ぶことができます。
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