We may earn an affiliate commission when you visit our partners.

Introduction to Large Language Models - 한국어

Google Cloud Training

대규모 언어 모델(LLM)이란 무엇이고, LLM을 활용할 수 있는 사용 사례로는 어떤 것이 있으며, 프롬프트 조정을 사용해 LLM 성능을 개선하는 방법을 알아보는 입문용 마이크로 학습 과정입니다. 또한 자체 생성형 AI 앱을 개발하는 데 도움이 되는 Google 도구에 대해서도 다룹니다.

Enroll now

Or subscribe to Coursera Plus

And get unlimited access to Coursera

What's inside

Syllabus

대규모 언어 모델 소개

이 모듈에서는 대규모 언어 모델(LLM)이란 무엇이고, LLM을 활용할 수 있는 사용 사례로는 어떤 것이 있으며, 프롬프트 조정을 사용해 LLM 성능을 개선하는 방법을 알아봅니다. 또한 자체 생성형 AI 앱을 개발하는 데 도움이 되는 Google 도구에 대해서도 다룹니다.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

탐구되는 주제는 거의 모든 산업에서 현재 표준화된 기술입니다

과정의 명확한 목표를 정의하고 이를 달성하는 방법에 대한 전략을 제공합니다

대규모 언어 모델의 특성을 분석하고 그 특성을 활용하여 다양한 분야에서 성능을 향상하는 방법에 대한 깊이 있는 이해를 제공합니다

Google Cloud에서 널리 사용되고 신뢰를 받는 도구의 활용법을 보여줍니다

자체 생성 AI 앱을 만드는 것과 같이 현실적인 상황의 문제점을 해결할 수 있는 실무적인 기술을 개발합니다

Save this course

Save Introduction to Large Language Models - 한국어 to your list so you can find it easily later:

Save

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 - 한국어 with these activities:

Review basic statistics and linear algebra concepts

Show steps

Reviewing these concepts will help provide a foundation for understanding the course material

Browse courses on Statistics

Show steps

Go over your lecture notes from previous courses in these two topics
Complete practice problems

Connect with professionals in the field

Show steps

Mentors can provide guidance and support throughout your learning journey

Show steps

Attend industry events and conferences
Reach out to professionals on LinkedIn
Ask for informational interviews

Google Cloud 도구 탐구하기

Show steps

자체 생성형 AI 앱 개발을 위한 Google 도구를 탐구하여 지식을 확장하여보세요.

Show steps

Google Cloud 플랫폼 설명서 및 자습서 검토하기
특정 도구를 위한 실습 세션 참여하기

Five other activities

Expand to see all activities and additional details

Show all eight activities

Follow tutorials on natural language processing and machine learning

Show steps

These tutorials will help enhance your understanding of the theoretical concepts behind the course

Browse courses on Natural Language Processing

Show steps

Find tutorials from reputable sources such as Coursera, edX, or YouTube
Complete the tutorials at your own pace
Take notes and ask questions

Practice using LLM APIs

Show steps

This practice will familiarize you with the practical application of LLM technology

Show steps

Sign up for an LLM platform
Explore the available APIs
Write code to interact with the APIs
Experiment with different prompts and parameters

자료 모음하기

Show steps

대규모 언어 모델, 프롬프트 조정 및 관련 도구에 대한 포괄적인 리소스 모음을 만들어 지식을 체계화하고 참조하기 쉽게 만들어보세요.

Show steps

연구 논문, 블로그 게시물 및 기타 정보 출처 수집하기
자료를 주제별로 구성 및 정리하기

Participate in peer review sessions

Show steps

Peer review will provide you with valuable feedback and insights

Show steps

Find a study group or partner
Share your work with your peers
Provide constructive feedback
Incorporate feedback into your own work

Develop a simple chatbot using an LLM API

Show steps

Building a chatbot will provide practical experience in applying LLM technology to solve a real-world problem

Show steps

Design the chatbot's functionality
Choose an appropriate LLM API
Develop the chatbot using the LLM API
Test and refine the chatbot

Career center

Learners who complete Introduction to Large Language Models - 한국어 will develop knowledge and skills that may be useful to these careers:

Data Scientist

As a Data Scientist, you will use your knowledge of large language models (LLMs) to develop innovative solutions to business problems. You will use LLMs to analyze data, identify trends, and make predictions. You will also use LLMs to create natural language processing (NLP) applications, such as chatbots and language translation systems.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

As a Machine Learning Engineer, you will use your knowledge of LLMs to develop and deploy machine learning models. You will use LLMs to improve the accuracy and efficiency of machine learning models. You will also use LLMs to develop new machine learning algorithms.

See salaries and explore the career path for Machine Learning Engineer

Natural Language Processing Engineer

As a Natural Language Processing Engineer, you will use your knowledge of LLMs to develop and deploy NLP applications. You will use LLMs to analyze text data, identify patterns, and extract meaning. You will also use LLMs to develop new NLP algorithms.

See salaries and explore the career path for Natural Language Processing Engineer

Software Engineer

As a Software Engineer, you will use your knowledge of LLMs to develop and deploy software applications. You will use LLMs to improve the quality and efficiency of software development. You will also use LLMs to develop new software development tools.

See salaries and explore the career path for Software Engineer

Product Manager

As a Product Manager, you will use your knowledge of LLMs to develop and launch new products. You will use LLMs to understand customer needs, identify market opportunities, and develop product roadmaps. You will also use LLMs to create product demos and marketing materials.

See salaries and explore the career path for Product Manager

Marketing Manager

As a Marketing Manager, you will use your knowledge of LLMs to develop and execute marketing campaigns. You will use LLMs to create marketing content, identify target audiences, and measure campaign performance. You will also use LLMs to develop new marketing strategies.

See salaries and explore the career path for Marketing Manager

Business Analyst

As a Business Analyst, you will use your knowledge of LLMs to analyze business processes and identify areas for improvement. You will use LLMs to create data models, develop process maps, and write business requirements documents. You will also use LLMs to present your findings to stakeholders.

See salaries and explore the career path for Business Analyst

Consultant

As a Consultant, you will use your knowledge of LLMs to help clients solve business problems. You will use LLMs to analyze data, identify trends, and make recommendations. You will also use LLMs to develop and implement solutions.

See salaries and explore the career path for Consultant

Technical Writer

As a Technical Writer, you will use your knowledge of LLMs to create technical documentation. You will use LLMs to write user guides, white papers, and training materials. You will also use LLMs to create marketing materials and website content.

See salaries and explore the career path for Technical Writer

Teacher

As a Teacher, you will use your knowledge of LLMs to teach students about language and literature. You will use LLMs to create lesson plans, develop teaching materials, and assess student learning.

See salaries and explore the career path for Teacher

Librarian

As a Librarian, you will use your knowledge of LLMs to catalog and organize information. You will use LLMs to create search tools, develop library collections, and provide reference services. You will also use LLMs to teach patrons about information literacy.

See salaries and explore the career path for Librarian

Editor

As an Editor, you will use your knowledge of LLMs to edit and proofread text. You will use LLMs to check for grammar and spelling errors, improve readability, and ensure consistency. You will also use LLMs to develop style guides and editorial policies.

See salaries and explore the career path for Editor

Translator

As a Translator, you will use your knowledge of LLMs to translate text from one language to another. You will use LLMs to ensure accuracy and fluency. You will also use LLMs to develop translation tools and resources.

See salaries and explore the career path for Translator

Journalist

As a Journalist, you will use your knowledge of LLMs to research and write news stories. You will use LLMs to gather information, verify facts, and write articles. You will also use LLMs to develop story ideas and create multimedia content.

See salaries and explore the career path for Journalist

Writer

As a Writer, you will use your knowledge of LLMs to create written content for a variety of purposes. You will use LLMs to write fiction, non-fiction, poetry, and screenplays. You will also use LLMs to develop writing skills and techniques.

See salaries and explore the career path for Writer

Reading list

We've selected 13 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 - 한국어.

Natural Language Processing with Transformers

Save

트랜스포머를 사용한 자연어 처리에 대한 입문서로서, 트랜스포머 아키텍처의 기본 사항에서 LLM의 구축 및 배포에 이르기까지 다양한 주제를 다룹니다.

Introduction to Large Language Models - 한국어

What's inside

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

Share

Similar courses