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Google Cloud
This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.
Read more
This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.
Read more
This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.
This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.
Register for this course and see more details by visiting:
OpenCourser.com/course/8plx2w/introduction
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What's inside
Syllabus
Introduction to Large Language Models
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores large language models, which drive innovations seen in industry and research globally
Focuses on industry use cases of large language models, which will help learners understand their direct professional applications
Covers prompt tuning techniques to enhance LLM performance, which aligns with industry best practices
Is taught by instructors from Google, a recognized leader in AI and LLM research
Introduces Google tools for AI development, which may provide learners with an advantage when using those tools in the future
Assumes no prior knowledge of LLMs, which makes it accessible to beginners
Save this course
Save Introduction to Large Language Models 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 Large Language Models with these
activities:
Visualize natural language data
Show steps
Begin by reviewing natural language processing (NLP) and data visualization techniques to ensure a strong foundation and refresh existing skills.
Browse courses on
Natural Language Processing
Show steps
-
Review the basics of NLP and data visualization using online resources or books.
-
Create a visualization of a small text dataset using a library or framework.
Organize and review course materials
Show steps
Enhance retention and understanding by organizing and reviewing lecture notes, assignments, and other course materials on a regular basis.
Show steps
-
Gather all course materials, including lecture notes, assignments, quizzes, and exams.
-
Organize the materials logically and systematically.
-
Review the materials regularly to reinforce your learning.
Assist other learners with LLM-related queries
Show steps
Strengthen your understanding of LLMs by sharing your knowledge and helping others navigate LLM-related concepts.
Browse courses on
Mentoring
Show steps
-
Join online forums or discussion groups related to LLMs.
-
Offer assistance to learners who have questions or need guidance.
-
Share your experiences, insights, and resources with others.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Explore Google's Large Language Model Benchmarks
Show steps
Enhance your understanding of LLM performance by exploring Google's collection of benchmarks and evaluation methods for LLMs.
Show steps
-
Visit the Google AI Benchmarks website (link provided in course materials).
-
Review the various LLM benchmarks and evaluation metrics.
-
Choose a benchmark or metric that aligns with your interests and explore it in-depth.
Practice prompt tuning with LLMs
Show steps
Gain hands-on experience with prompt tuning by practicing on different LLM platforms and experimenting with various prompts.
Browse courses on
Prompt Tuning
Show steps
-
Choose an LLM platform (e.g., ChatGPT, GPT-3, BLOOM).
-
Write a series of prompts for a specific task or use case.
-
Experiment with different prompt variations, such as length, structure, and tone.
-
Analyze the LLM's responses and refine your prompts accordingly.
Attend a workshop on Generative AI applications
Show steps
Expand your knowledge of Gen AI by attending a workshop led by experts in the field.
Browse courses on
Generative AI
Show steps
-
Explore upcoming workshops related to Generative AI applications.
-
Register for a workshop that aligns with your interests.
-
Attend the workshop and actively participate in discussions and exercises.
Build a simple Gen AI application
Show steps
Solidify your understanding of Gen AI by applying your knowledge to develop a functional Gen AI application.
Browse courses on
Generative AI
Show steps
-
Identify a specific problem or use case that Gen AI can address.
-
Choose appropriate Google tools and technologies for your application.
-
Design and develop your application using best practices for Gen AI development.
-
Test and iterate on your application to improve its performance and user experience.
Participate in an AI hackathon or competition
Show steps
Challenge yourself and apply your skills in a practical setting by participating in an AI hackathon or competition centered around LLMs.
Show steps
-
Identify and register for an AI hackathon or competition that aligns with your interests.
-
Form a team or work individually on a project.
-
Develop an innovative AI solution using LLMs.
-
Present your solution to a panel of judges and receive feedback.
Visualize natural language data
Show steps
Begin by reviewing natural language processing (NLP) and data visualization techniques to ensure a strong foundation and refresh existing skills.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Review the basics of NLP and data visualization using online resources or books.
- Create a visualization of a small text dataset using a library or framework.
Organize and review course materials
Show steps
Enhance retention and understanding by organizing and reviewing lecture notes, assignments, and other course materials on a regular basis.
Show steps
Show steps
Show steps
- Gather all course materials, including lecture notes, assignments, quizzes, and exams.
- Organize the materials logically and systematically.
- Review the materials regularly to reinforce your learning.
Assist other learners with LLM-related queries
Show steps
Strengthen your understanding of LLMs by sharing your knowledge and helping others navigate LLM-related concepts.
Browse courses on
Mentoring
Show steps
Show steps
Show steps
- Join online forums or discussion groups related to LLMs.
- Offer assistance to learners who have questions or need guidance.
- Share your experiences, insights, and resources with others.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Explore Google's Large Language Model Benchmarks
Show steps
Enhance your understanding of LLM performance by exploring Google's collection of benchmarks and evaluation methods for LLMs.
Show steps
Show steps
Show steps
- Visit the Google AI Benchmarks website (link provided in course materials).
- Review the various LLM benchmarks and evaluation metrics.
- Choose a benchmark or metric that aligns with your interests and explore it in-depth.
Practice prompt tuning with LLMs
Show steps
Gain hands-on experience with prompt tuning by practicing on different LLM platforms and experimenting with various prompts.
Browse courses on
Prompt Tuning
Show steps
Show steps
Show steps
- Choose an LLM platform (e.g., ChatGPT, GPT-3, BLOOM).
- Write a series of prompts for a specific task or use case.
- Experiment with different prompt variations, such as length, structure, and tone.
- Analyze the LLM's responses and refine your prompts accordingly.
Attend a workshop on Generative AI applications
Show steps
Expand your knowledge of Gen AI by attending a workshop led by experts in the field.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
- Explore upcoming workshops related to Generative AI applications.
- Register for a workshop that aligns with your interests.
- Attend the workshop and actively participate in discussions and exercises.
Build a simple Gen AI application
Show steps
Solidify your understanding of Gen AI by applying your knowledge to develop a functional Gen AI application.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
- Identify a specific problem or use case that Gen AI can address.
- Choose appropriate Google tools and technologies for your application.
- Design and develop your application using best practices for Gen AI development.
- Test and iterate on your application to improve its performance and user experience.
Participate in an AI hackathon or competition
Show steps
Challenge yourself and apply your skills in a practical setting by participating in an AI hackathon or competition centered around LLMs.
Show steps
Show steps
Show steps
- Identify and register for an AI hackathon or competition that aligns with your interests.
- Form a team or work individually on a project.
- Develop an innovative AI solution using LLMs.
- Present your solution to a panel of judges and receive feedback.
Career center
Learners who complete Introduction to Large Language Models will develop knowledge and skills
that may be useful to these careers:
Content Writer
Content Writer
Large language models are revolutionizing the way content is created. By taking this course, you will learn how to use LLMs to generate high-quality, engaging content that can help you achieve your business goals. You will also learn how to use prompt tuning to improve the accuracy and relevance of your LLM-generated content. This course is essential for any content writer who wants to stay ahead of the curve and use LLMs to create content that drives results.
Marketing Manager
Marketing Manager
Large language models are quickly changing the marketing landscape. By taking this course, you will gain the knowledge and skills necessary to use LLMs to create effective marketing campaigns that can reach and engage your target audience. You will also learn how to use prompt tuning to improve the performance of your LLM-powered marketing initiatives. This course is a must-have for any marketing professional who wants to stay ahead of the curve and use LLMs to drive business growth.
Social Media Manager
Social Media Manager
Large language models are quickly changing the way social media is used. By taking this course, you will learn how to use LLMs to create engaging social media content that can help you reach and engage your target audience. You will also learn how to use prompt tuning to improve the performance of your LLM-powered social media campaigns. This course is essential for any social media manager who wants to stay ahead of the curve and use LLMs to drive business growth.
SEO Specialist
SEO Specialist
Large language models are becoming increasingly important for SEO. By taking this course, you will learn how to use LLMs to optimize your website for search engines. You will also learn how to use prompt tuning to improve the relevance and quality of your LLM-generated content. This course is essential for any SEO specialist who wants to stay ahead of the curve and use LLMs to drive organic traffic to their website.
Data Analyst
Data Analyst
Large language models are revolutionizing the way data is analyzed. By taking this course, you will learn how to use LLMs to automate data analysis tasks, generate insights from data, and improve the accuracy of your data-driven decision-making. You will also learn how to use prompt tuning to improve the performance of your LLM-powered data analysis pipelines. This course is essential for any data analyst who wants to stay ahead of the curve and use LLMs to drive business value.
Product Manager
Product Manager
Large language models are becoming increasingly important for product management. By taking this course, you will learn how to use LLMs to gather customer feedback, generate product ideas, and improve the user experience of your products. You will also learn how to use prompt tuning to improve the accuracy and relevance of your LLM-generated insights. This course is essential for any product manager who wants to stay ahead of the curve and use LLMs to build better products.
Consultant
Consultant
Large language models are quickly changing the way consulting services are delivered. By taking this course, you will learn how to use LLMs to generate consulting reports, provide consulting advice, and improve the quality of your consulting services. You will also learn how to use prompt tuning to improve the accuracy and relevance of your LLM-generated consulting insights. This course is essential for any consultant who wants to stay ahead of the curve and use LLMs to drive business growth.
Technical Writer
Technical Writer
Large language models are quickly changing the way technical documentation is created. By taking this course, you will learn how to use LLMs to generate technical documentation, translate technical documents, and improve the clarity and accuracy of your technical writing. You will also learn how to use prompt tuning to improve the performance of your LLM-powered technical writing tools. This course is essential for any technical writer who wants to stay ahead of the curve and use LLMs to create better technical documentation.
Entrepreneur
Entrepreneur
Large language models are becoming increasingly important for entrepreneurs. By taking this course, you will learn how to use LLMs to generate business ideas, develop business plans, and improve the success of your entrepreneurial ventures. You will also learn how to use prompt tuning to improve the accuracy and relevance of your LLM-generated entrepreneurial insights. This course is essential for any entrepreneur who wants to stay ahead of the curve and use LLMs to build a successful business.
UX Designer
UX Designer
Large language models are becoming increasingly important for UX design. By taking this course, you will learn how to use LLMs to generate user interface ideas, prototype user interfaces, and improve the user experience of your digital products. You will also learn how to use prompt tuning to improve the accuracy and relevance of your LLM-generated UX designs. This course is essential for any UX designer who wants to stay ahead of the curve and use LLMs to create better user experiences.
Research Scientist
Research Scientist
Large language models are revolutionizing the way research is conducted. By taking this course, you will learn how to use LLMs to generate research ideas, gather data, and analyze research results. You will also learn how to use prompt tuning to improve the accuracy and relevance of your LLM-generated research insights. This course is essential for any research scientist who wants to stay ahead of the curve and use LLMs to drive scientific discovery.
Machine Learning Engineer
Machine Learning Engineer
Large language models are becoming increasingly important for machine learning. By taking this course, you will learn how to use LLMs to train machine learning models, generate synthetic data, and improve the performance of your machine learning algorithms. You will also learn how to use prompt tuning to improve the accuracy and relevance of your LLM-generated machine learning models. This course is essential for any machine learning engineer who wants to stay ahead of the curve and use LLMs to build better machine learning models.
Academic Researcher
Academic Researcher
Large language models are revolutionizing the way academic research is conducted. By taking this course, you will learn how to use LLMs to generate research ideas, gather research data, and analyze research results. You will also learn how to use prompt tuning to improve the accuracy and relevance of your LLM-generated research insights. This course is essential for any academic researcher who wants to stay ahead of the curve and use LLMs to drive academic discovery.
Business Analyst
Business Analyst
Large language models are revolutionizing the way business analysis is conducted. By taking this course, you will learn how to use LLMs to gather business requirements, analyze business data, and improve the accuracy and efficiency of your business analysis processes. You will also learn how to use prompt tuning to improve the performance of your LLM-powered business analysis tools. This course is essential for any business analyst who wants to stay ahead of the curve and use LLMs to drive business value.
Software Engineer
Software Engineer
Large language models are quickly changing the way software is developed. By taking this course, you will learn how to use LLMs to automate coding tasks, generate code snippets, and improve the quality of your code. You will also learn how to use prompt tuning to improve the accuracy and relevance of your LLM-generated code. This course is essential for any software engineer who wants to stay ahead of the curve and use LLMs to build better software.
For more career information including salaries, visit:
OpenCourser.com/course/8plx2w/introduction
Reading list
We've selected ten 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.
Save
Provides a comprehensive overview of deep learning, which is the foundation of LLMs. It valuable resource for anyone looking to understand the theoretical underpinnings of LLMs.
Provides a comprehensive overview of NLP, which is the field that LLMs are used for. It valuable resource for anyone looking to understand the broader context of LLMs.
Provides a practical guide to machine learning with Scikit-Learn, Keras, and TensorFlow. It covers a wide range of topics, including data preparation, model training, and evaluation. It valuable resource for anyone who wants to get started with machine learning.
Provides a comprehensive overview of speech and language processing, which are two of the main applications of LLMs. It valuable resource for anyone looking to understand the practical uses of LLMs.
Provides a comprehensive overview of statistical learning, which is the foundation of LLMs. It valuable resource for anyone looking to understand the theoretical underpinnings of LLMs.
Provides a comprehensive overview of pattern recognition and machine learning, which are the foundations of LLMs. It valuable resource for anyone looking to understand the theoretical underpinnings of LLMs.
Provides a comprehensive overview of the Natural Language Toolkit (NLTK). It covers a wide range of topics, including NLTK fundamentals, NLTK applications, and NLTK research. It valuable resource for anyone who wants to learn more about this powerful NLP toolkit.
Provides a comprehensive overview of machine learning from a probabilistic perspective, which is the foundation of LLMs. It valuable resource for anyone looking to understand the theoretical underpinnings of LLMs.
Provides a practical guide to deep learning with Python, which is the programming language that is most commonly used to develop LLMs. It valuable resource for anyone looking to develop their own LLM applications.
Provides a comprehensive overview of natural language processing with Python. It covers a wide range of topics, including Python fundamentals, NLP fundamentals, and NLP applications. It valuable resource for anyone who wants to learn more about this field.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/8plx2w/introduction
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Time
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Level
Introductory
Via
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Instructor
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Language
English
Good to know
Explores large language models, which drive innovations seen in industry and research globally
Focuses on industry use cases of large language models, which will help learners understand their direct professional applications
Covers prompt tuning techniques to enhance LLM performance, which aligns with industry best practices
Is taught by instructors from Google, a recognized leader in AI and LLM research
Introduces Google tools for AI development, which may provide learners with an advantage when using those tools in the future
Assumes no prior knowledge of LLMs, which makes it accessible to beginners
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