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Introduction to Large Language Models with Google Cloud

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.

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

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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Activities

Coming soon We're preparing activities for Introduction to Large Language Models with Google Cloud. These are activities you can do either before, during, or after a course.

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 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 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
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 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 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 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
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 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
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 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 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
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
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 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 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.

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.
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.
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.

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