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Google Cloud Training
Take Udacity's free Cloud Introduction to Large Language Models Course by Google and learn what large language models are and their use cases.
Register for this course and see more details by visiting:
OpenCourser.com/course/a6iuev/introduction
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What's inside
Syllabus
This is an introductory 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.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Well-suited to beginners seeking an introduction to large language models (LLMs)
Part of a larger program by Google, a company known for its advancements in AI and LLMs
Taught by Google Cloud Training, recognized for its expertise in cloud computing and AI
Focuses on practical applications of LLMs, making it relevant for those interested in using LLMs for real-world tasks
May require some prior knowledge of machine learning or AI concepts
Does not cover advanced topics in LLMs or their underlying algorithms
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Save Introduction to Large Language Models with Google Cloud 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 Google Cloud with these
activities:
Review Statistical and Machine Learning Concepts
Show steps
Strengthen your foundation by reviewing statistical and machine learning concepts that support LLM understanding.
Browse courses on
Statistics
Show steps
-
Review your notes or materials from previous courses or workshops on statistics and machine learning.
-
Read introductory articles or blog posts to refresh your knowledge on key concepts.
-
Complete online quizzes or exercises to test your understanding.
Follow Tutorials on Large Language Models
Show steps
Explore LLMs further by following guided tutorials and demonstrations.
Browse courses on
Large Language Models
Show steps
-
Search for online tutorials or workshops on LLM fundamentals.
-
Follow along with the tutorials, completing exercises and activities to solidify your understanding.
-
Explore the documentation and resources provided by LLM platforms or providers.
Practice Prompt Tuning Exercises
Show steps
Develop proficiency in prompt tuning by engaging in hands-on exercises.
Browse courses on
Prompt Tuning
Show steps
-
Find online resources or platforms that provide interactive prompt tuning exercises.
-
Practice writing effective prompts for LLMs, focusing on clarity, specificity, and purpose.
-
Evaluate the results of your prompts and refine them based on the LLM's responses.
Show all three activities
Review Statistical and Machine Learning Concepts
Show steps
Strengthen your foundation by reviewing statistical and machine learning concepts that support LLM understanding.
Browse courses on
Statistics
Show steps
Show steps
Show steps
- Review your notes or materials from previous courses or workshops on statistics and machine learning.
- Read introductory articles or blog posts to refresh your knowledge on key concepts.
- Complete online quizzes or exercises to test your understanding.
Follow Tutorials on Large Language Models
Show steps
Explore LLMs further by following guided tutorials and demonstrations.
Browse courses on
Large Language Models
Show steps
Show steps
Show steps
- Search for online tutorials or workshops on LLM fundamentals.
- Follow along with the tutorials, completing exercises and activities to solidify your understanding.
- Explore the documentation and resources provided by LLM platforms or providers.
Practice Prompt Tuning Exercises
Show steps
Develop proficiency in prompt tuning by engaging in hands-on exercises.
Browse courses on
Prompt Tuning
Show steps
Show steps
Show steps
- Find online resources or platforms that provide interactive prompt tuning exercises.
- Practice writing effective prompts for LLMs, focusing on clarity, specificity, and purpose.
- Evaluate the results of your prompts and refine them based on the LLM's responses.
Show all three activities
Career center
Learners who complete Introduction to Large Language Models with Google Cloud will develop knowledge and skills
that may be useful to these careers:
Natural Language Processing Engineer
Natural Language Processing Engineer
Natural Language Processing Engineers develop and implement systems that can understand and generate human language. This course provides a solid foundation in LLMs, which are becoming increasingly important in the field of NLP. By learning about LLMs and how to use them effectively, you can gain a competitive edge in this rapidly growing field.
Research Scientist
Research Scientist
Research Scientists conduct research to advance the field of computer science. This course provides a foundation in LLMs, which are becoming increasingly important in the field of AI research. By learning about LLMs and how to use them effectively, you can gain a competitive edge in this rapidly growing field.
AI Engineer
AI Engineer
As an AI Engineer, you will be tasked with designing, developing, and implementing AI solutions for various industries. This course provides a solid foundation in Large Language Models (LLMs), which are becoming increasingly important in the field of AI. By learning about LLMs and how to use them effectively, you can gain a competitive edge in this rapidly growing field.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build and deploy machine learning models to solve complex problems. This course provides a foundation in LLMs, which are becoming increasingly important in the field of machine learning. By learning about LLMs and how to use them effectively, you can gain a competitive edge in this rapidly growing field.
Data Scientist
Data Scientist
Data Scientists are responsible for collecting, analyzing, and interpreting data to help businesses make informed decisions. This course can be particularly useful for Data Scientists who want to learn more about LLMs and how they can be used to enhance data analysis and modeling tasks.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course provides a foundation in LLMs, which are becoming increasingly important in the field of software development. By learning about LLMs and how to use them effectively, you can gain a competitive edge in this rapidly growing field.
Consultant
Consultant
Consultants provide advice and guidance to businesses on a variety of topics. This course can be particularly useful for Consultants who want to learn more about LLMs and how they can be used to enhance their consulting services.
Technical Writer
Technical Writer
Technical Writers create documentation and other materials to help people understand technical products and services. This course can be particularly useful for Technical Writers who want to learn more about LLMs and how they can be used to enhance their writing and communication skills.
Entrepreneur
Entrepreneur
Entrepreneurs start and run their own businesses. This course can be particularly useful for Entrepreneurs who want to learn more about LLMs and how they can be used to enhance their business development and marketing.
UX Designer
UX Designer
UX Designers design and evaluate user interfaces for websites, apps, and other digital products. This course can be particularly useful for UX Designers who want to learn more about LLMs and how they can be used to enhance their design and evaluation processes.
Product Manager
Product Manager
Product Managers are responsible for developing and managing products. This course can be particularly useful for Product Managers who want to learn more about LLMs and how they can be used to enhance product development and marketing.
Salesperson
Salesperson
Salespeople sell products and services to customers. This course can be particularly useful for Salespeople who want to learn more about LLMs and how they can be used to enhance their sales pitches and negotiations.
Marketer
Marketer
Marketers develop and execute marketing campaigns to promote products and services. This course can be particularly useful for Marketers who want to learn more about LLMs and how they can be used to enhance their marketing efforts.
Data Analyst
Data Analyst
Data Analysts collect, analyze, and interpret data to help businesses make informed decisions. This course can be particularly useful for Data Analysts who want to learn more about LLMs and how they can be used to enhance data analysis and modeling tasks.
Business Analyst
Business Analyst
Business Analysts help businesses understand their needs and develop solutions to improve their operations. This course can be particularly useful for Business Analysts who want to learn more about LLMs and how they can be used to enhance data analysis and modeling tasks.
For more career information including salaries, visit:
OpenCourser.com/course/a6iuev/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 Large Language Models with Google Cloud.
Provides a rigorous treatment of convex optimization theory and algorithms. It will equip learners with a solid foundation in optimization techniques used in machine learning and LLM training, enabling them to understand and implement advanced optimization methods.
Offers a comprehensive overview of the mathematical foundations of machine learning. It will provide learners with a strong mathematical background, enabling them to grasp the technical aspects of LLMs and perform advanced analysis.
As a comprehensive textbook on speech and language processing, this book provides an overview of fundamental concepts and techniques. It will equip learners with background knowledge in NLP and prepare them for deeper exploration of LLMs in the course.
Save
As a foundational text in deep learning, this book will strengthen learners' understanding of the underlying principles and algorithms used in LLMs. It provides a comprehensive overview of deep learning architectures, training techniques, and applications.
Provides a solid foundation in statistical learning and machine learning concepts. It will equip learners with a deeper understanding of the statistical underpinnings of LLMs and prepare them for further exploration of advanced LLM techniques.
Offers a comprehensive overview of Gaussian processes, a powerful non-parametric machine learning technique. It will broaden learners' understanding of machine learning models beyond LLMs and provide insights into advanced modeling approaches used in various domains.
Offers a practical approach to building and deploying LLM-based applications. Reading it alongside the course will provide learners with valuable insights into the practical aspects of LLM implementation and real-world use cases.
Offers an in-depth exploration of natural language understanding, covering various techniques and applications. It will broaden learners' understanding of NLP concepts beyond LLMs and provide a deeper context for the course's focus on LLM-based solutions.
Save
Supplementing the course's focus on LLM applications, this book provides practical guidance on text mining techniques and their implementation using R. It will enhance learners' understanding of how LLMs can be used for text analysis and information extraction tasks.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/a6iuev/introduction
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Effort
45 minutes
Via
Udacity
Instructor
Google Cloud Training
Language
English
Good to know
Well-suited to beginners seeking an introduction to large language models (LLMs)
Part of a larger program by Google, a company known for its advancements in AI and LLMs
Taught by Google Cloud Training, recognized for its expertise in cloud computing and AI
Focuses on practical applications of LLMs, making it relevant for those interested in using LLMs for real-world tasks
May require some prior knowledge of machine learning or AI concepts
Does not cover advanced topics in LLMs or their underlying algorithms
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