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Introduction to Large Language Models - 简体中文
Google Cloud Training
Google Cloud Training
这是一节入门级微学习课程，探讨什么是大型语言模型 (LLM)、适合的应用场景以及如何使用提示调整来提升 LLM 性能。该课程还介绍了可以帮助您开发自己的 Gen AI 应用的各种 Google 工具。
Register for this course and see more details by visiting:
OpenCourser.com/course/o8ldxp/introduction
What's inside
Syllabus
大型语言模型简介
本单元探讨什么是大型语言模型 (LLM)、适合的应用场景以及如何使用提示调整来提升 LLM 性能。该课程还介绍了可以帮助您开发自己的 Gen AI 应用的各种 Google 工具。
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
深入了解 Gen AI， 可帮助学生提升在不断发展的领域中的竞争力。
利用 Google 工具，学生可以开发自己的生成式人工智能应用，这为他们提供了宝贵的实践经验。
通过提示调整来提升 LLM 性能，可以让学生掌握一项关键技能，从而优化其 Gen AI 应用。
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Activities
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Introduction to Large Language Models - 简体中文.
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Career center
Learners who complete Introduction to Large Language Models - 简体中文 will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for designing, developing, and optimizing machine learning systems. This course can help individuals interested in Machine Learning Engineering build a foundation in large language models, which are heavily leveraged in this field. The course also covers various tools and resources provided by Google that can help Machine Learning Engineers jumpstart their work on generative AI applications.
Natural Language Processing Engineer
Natural Language Processing Engineer
Natural Language Processing Engineers are responsible for developing and maintaining software that can understand and generate human language. This course may help aspiring Natural Language Processing Engineers build a foundation in large language models, which are at the core of this field. The course provides practical tips on how to optimize large language models through prompt engineering, which can prove particularly valuable for Natural Language Processing Engineers.
Computational Linguist
Computational Linguist
Computational Linguists are responsible for studying the relationship between natural language and computation. This course can help aspiring Computational Linguists develop a strong foundation in large language models. The course also provides practical tips on how to use large language models for tasks such as text classification and generation, which can be beneficial for Computational Linguists.
Artificial Intelligence Researcher
Artificial Intelligence Researcher
Artificial Intelligence Researchers are responsible for developing new and innovative artificial intelligence algorithms and applications. This course may be useful for entry-level Artificial Intelligence Researchers who are interested in exploring large language models. The course provides an overview of the fundamental concepts and applications of large language models, which can be helpful for researchers in this field.
Software Engineer
Software Engineer
Software Engineers are responsible for designing, developing, and maintaining software applications. This course may be useful for Software Engineers who are interested in building generative AI applications. The course provides an overview of the latest advancements in large language models and shares best practices for prompt engineering, which can help Software Engineers write efficient and effective prompts.
Product Manager
Product Manager
Product Managers are responsible for defining and managing the development of software products. This course may be useful for Product Managers who are interested in incorporating large language models into their products. The course provides practical tips on how to identify use cases for large language models and how to design products that leverage these technologies effectively.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts are responsible for developing and implementing quantitative models to analyze financial data. This course may be useful for Quantitative Analysts who are interested in using large language models to improve their models. The course provides practical tips on how to use large language models for tasks such as time series forecasting and risk analysis, which can be beneficial for Quantitative Analysts.
Content Creator
Content Creator
Content Creators are responsible for creating and publishing content for various platforms and audiences. This course may be useful for Content Creators who are interested in using large language models to create high-quality and engaging content. The course also covers Google tools that can help automate parts of the content creation process using large language models, which can improve efficiency.
Marketing Manager
Marketing Manager
Marketing Managers are responsible for planning and executing marketing campaigns. This course may be useful for Marketing Managers who are interested in using large language models to improve the effectiveness of their campaigns. The course provides practical tips on how to use large language models for tasks such as content creation and marketing analytics, which can help Marketing Managers achieve better results.
Business Analyst
Business Analyst
Business Analysts are responsible for analyzing business processes and identifying opportunities for improvement. This course can help aspiring Business Analysts build a foundation in large language models, which can be useful for tasks such as market research and competitive analysis. The course also shares case studies of real-world applications of large language models in a business context.
Data Scientist
Data Scientist
Data Scientists are responsible for collecting, cleaning, and safeguarding data according to industry standards. This course can help aspiring Data Scientists build a foundation in large language models, which may allow them to explore and analyze complex datasets more efficiently. The course also covers applications of large language models that could prove useful in this role.
UX Designer
UX Designer
UX Designers are responsible for designing and evaluating user experiences for software products. This course may be useful for UX Designers who are interested in using large language models to improve the user experience of their products. The course provides practical tips on how to use large language models for tasks such as user research and prototyping, which can improve the quality of user experience.
Consultant
Consultant
Consultants are responsible for providing advice and guidance to businesses and organizations. This course may be useful for Consultants who are interested in advising their clients on how to use large language models. The course provides practical tips on how to identify use cases for large language models and how to develop a strategy for implementing these technologies.
Data Analyst
Data Analyst
Data Analysts are responsible for analyzing business and industry-related data. They help organizations make informed decisions. This course may help entry-level Data Analysts understand how large language models are created and applied to different use cases, which could allow them to perform exploratory data analysis more efficiently. The course also covers prompt engineering techniques which Data Analysts may find useful in building efficient queries.
Entrepreneur
Entrepreneur
Entrepreneurs are responsible for starting and running their own businesses. This course may be useful for Entrepreneurs who are interested in using large language models in their business. The course provides practical tips on how to identify use cases for large language models and how to develop a strategy for implementing these technologies.
For more career information including salaries, visit:
OpenCourser.com/course/o8ldxp/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 - 简体中文.
Save
本书是人工智能领域的经典教科书，提供了人工智能的基础知识和前沿进展，对于理解大语言模型所依赖的人工智能原理有帮助。
这本书提供了使用 Transformer 模型进行机器学习的实用指南，它涵盖了模型训练、微调和部署。
这本书提供了使用神经网络进行自然语言处理的全面介绍，它涵盖了基础知识、模型架构和应用程序。
这本书提供了深入的自然语言处理教程，它涵盖了从基础知识到高级模型和应用程序的所有内容。
这本书提供了对循环神经网络的全面介绍，它涵盖了基本概念、模型架构和训练技术。
Save
这本书提供了对深度学习的全面介绍，它涵盖了基础知识、模型架构和训练技术。
这本书提供了对自然语言处理的全面介绍，它涵盖了基础知识、工具和应用程序。
For more information about how these books relate to this course, visit:
OpenCourser.com/course/o8ldxp/introduction
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Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
中文
Transcript
English
Good to know
深入了解 Gen AI， 可帮助学生提升在不断发展的领域中的竞争力。
利用 Google 工具，学生可以开发自己的生成式人工智能应用，这为他们提供了宝贵的实践经验。
通过提示调整来提升 LLM 性能，可以让学生掌握一项关键技能，从而优化其 Gen AI 应用。
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