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Introduction to Large Language Models

Google Cloud Training

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.

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What's inside

Syllabus

Introduction to Large Language Models
This module 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.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores large language models (LLM), an industry standard for natural language processing
Covers prompt tuning, a technique for enhancing LLM performance
Provides hands-on experience with Google tools for developing Gen AI applications
Taught by Google Cloud Training, renowned for expertise in cloud computing and AI
May require knowledge of programming and natural language processing concepts

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Activities

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

Career center

Learners who complete Introduction to Large Language Models will develop knowledge and skills that may be useful to these careers:
Data Scientist
A Data Scientist develops and builds analytical models for improving insights into the line of business. They provide actionable insights for stakeholders and make data-driven recommendations. This course can help build a foundation in large language models, which are increasingly used in data science. By understanding the capabilities and limitations of LLMs, Data Scientists can leverage them effectively in their work.
Machine Learning Engineer
Machine Learning Engineers design, develop, and maintain machine learning models for a variety of applications. This course can help build a foundation in large language models, which are a powerful tool for training machine learning models. By understanding how LLMs work and how to use them effectively, Machine Learning Engineers can improve the accuracy and performance of their models.
Software Engineer
Software Engineers design, develop, and maintain software applications. This course can help build a foundation in large language models, which are increasingly being used in software development. By understanding how LLMs work and how to use them effectively, Software Engineers can create more powerful and efficient applications.
Product Manager
Product Managers are responsible for developing and managing the lifecycle of a product. This course can help build a foundation in large language models, which are increasingly being used in product development. By understanding how LLMs work and how to use them effectively, Product Managers can create better products that meet the needs of their users.
Data Analyst
Data Analysts collect, clean, and analyze data to help organizations make informed decisions. This course can help build a foundation in large language models, which are increasingly being used in data analysis. By understanding how LLMs work and how to use them effectively, Data Analysts can gain deeper insights into data and make better recommendations for action.
Business Analyst
Business Analysts help organizations improve their performance by analyzing data and identifying opportunities for improvement. This course can help build a foundation in large language models, which are increasingly being used in business analysis. By understanding how LLMs work and how to use them effectively, Business Analysts can gain deeper insights into data and make better recommendations for improvement.
Content Writer
Content Writers create written content for websites, blogs, and other online platforms. This course can help build a foundation in large language models, which are increasingly being used in content writing. By understanding how LLMs work and how to use them effectively, Content Writers can create more engaging and informative content.
Technical Writer
Technical Writers create documentation for software, hardware, and other technical products. This course can help build a foundation in large language models, which are increasingly being used in technical writing. By understanding how LLMs work and how to use them effectively, Technical Writers can create more clear and concise documentation.
Marketing Manager
Marketing Managers develop and execute marketing campaigns to promote products and services. This course can help build a foundation in large language models, which are increasingly being used in marketing. By understanding how LLMs work and how to use them effectively, Marketing Managers can create more effective marketing campaigns.
Customer Success Manager
Customer Success Managers help customers achieve their goals with a product or service. This course may be useful for Customer Success Managers who want to understand how large language models can be used to improve customer satisfaction. By understanding how LLMs work and how to use them effectively, Customer Success Managers can provide better support to customers, identify and resolve problems, and build stronger relationships with customers.
Sales Manager
Sales Managers lead and manage sales teams to achieve sales goals. This course may be useful for Sales Managers who want to understand how large language models can be used to improve sales performance. By understanding how LLMs work and how to use them effectively, Sales Managers can identify and qualify leads, close deals, and build stronger relationships with customers.
Project Manager
Project Managers plan and execute projects to achieve specific goals. This course may be useful for Project Managers who want to understand how large language models can be used to improve project management. By understanding how LLMs work and how to use them effectively, Project Managers can create better project plans, track progress, and manage risks.
Quality Assurance Analyst
Quality Assurance Analysts test software and other products to ensure that they meet quality standards. This course may be useful for Quality Assurance Analysts who want to understand how large language models can be used to improve testing. By understanding how LLMs work and how to use them effectively, Quality Assurance Analysts can create better test cases, identify defects, and improve the quality of software products.
Research Analyst
Research Analysts conduct research to inform decision-making. This course may be useful for Research Analysts who want to understand how large language models can be used to improve research. By understanding how LLMs work and how to use them effectively, Research Analysts can gather data, analyze data, and draw insights more efficiently.
Operations Manager
Operations Managers oversee the day-to-day operations of a business. This course may be useful for Operations Managers who want to understand how large language models can be used to improve operational efficiency. By understanding how LLMs work and how to use them effectively, Operations Managers can identify and streamline processes, reduce costs, and improve customer satisfaction.

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.
Provides a comprehensive overview of large language models (LLMs), covering the history, architecture, and applications of LLMs. It valuable resource for anyone interested in learning more about LLMs.
Provides a comprehensive introduction to deep learning, covering the basics of neural networks, convolutional neural networks, recurrent neural networks, and other advanced topics. It valuable resource for both beginners and experienced practitioners.
Provides a comprehensive overview of speech and language processing, covering the basics of speech recognition, natural language processing, and other advanced topics. It valuable resource for both beginners and experienced practitioners.
Provides a comprehensive overview of computer vision, covering the basics of image processing, feature detection, and other advanced topics. It valuable resource for both beginners and experienced practitioners.
Provides a comprehensive overview of natural language processing (NLP) in Python, covering the basics of NLP, text mining, and other advanced topics. It valuable resource for both beginners and experienced practitioners.
Provides a comprehensive overview of AI, covering the history, philosophy, and applications of AI. It valuable resource for anyone interested in learning more about AI.
Provides a concise overview of robotics, covering the history, applications, and challenges of robotics. It valuable resource for anyone interested in learning more about robotics.
Explores the potential risks and benefits of superintelligence, and discusses the importance of developing AI that is safe and beneficial to humanity.
Explores the challenges of aligning AI systems with human values, and discusses the importance of developing AI that is safe and beneficial to humanity.

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