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Introduction to Large Language Models - Français

Google Cloud Training

Ce cours de micro-apprentissage, qui s'adresse aux débutants, explique ce que sont les grands modèles de langage (LLM). Il inclut des cas d'utilisation et décrit comment améliorer les performances des LLM grâce au réglage des invites. Il présente aussi les outils Google qui vous aideront à développer vos propres applications d'IA générative.

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What's inside

Syllabus

Présentation des grands modèles de langage
Ce module explique ce que sont les grands modèles de langage (LLM), présente des cas d'utilisation et décrit comment le réglage des invites permet d'améliorer les performances des LLM. Il présente aussi les outils Google qui vous aideront à développer vos propres applications d'IA générative.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Ce cours s'adresse aux débutants et explique les concepts de base des grands modèles de langage (LLM)
Il fournit des cas d'utilisation pratiques et des conseils pour améliorer les performances des LLM en ajustant les invites
Ce cours présente les outils Google qui permettent de développer des applications d'IA générative
Il s'agit d'un cours de micro-apprentissage, ce qui le rend accessible aux personnes disposant de peu de temps

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Career center

Learners who complete Introduction to Large Language Models - Français will develop knowledge and skills that may be useful to these careers:
Data Scientist
A Data Scientist can take this Introduction to Large Language Models - Français course to help build a foundation for their work in developing and using artificial intelligence and machine learning models. This course will provide a comprehensive overview of the theory and practice of machine learning, with a focus on deep learning and natural language processing. The course will cover a variety of topics, including data preprocessing, feature engineering, model selection, and model evaluation. Additionally, this course will provide students with the opportunity to gain hands-on experience with machine learning tools and techniques by completing a series of coding assignments.
Machine Learning Engineer
Similarly, this Introduction to Large Language Models - Français course may be of use to a Machine Learning Engineer as they work with machine learning models. This course will provide a broad overview of machine learning, from its theoretical foundations to its practical applications. Students will learn about different types of machine learning algorithms, how to train and evaluate models, and how to apply machine learning to real-world problems. This course may be especially helpful for Machine Learning Engineers who are new to the field or who want to learn more about deep learning and natural language processing.
Software Engineer
This Introduction to Large Language Models - Français course could be useful for a Software Engineer looking to work on AI-driven projects. This course will introduce students to the basics of artificial intelligence, from its history and development to its potential applications in various industries. Students will learn about different types of AI algorithms, how to develop and train AI models, and how to evaluate their performance.
Data Analyst
A Data Analyst may find this Introduction to Large Language Models - Français course helpful as they work with data to solve business problems. This course will introduce fundamental concepts in statistics and probability, with an emphasis on data analysis. Students will learn how to collect, clean, and analyze data, and how to communicate their findings effectively.
Business Analyst
For a Business Analyst looking to use AI and data to improve business processes and outcomes, this Introduction to Large Language Models - Français course may be useful. This course will provide a comprehensive overview of the field of business analytics, including data analysis, data mining, and predictive modeling. Students will learn how to use data to identify business opportunities, solve problems, and make better decisions.
Product Manager
A Product Manager who wants to build AI-powered products might find this Introduction to Large Language Models - Français course useful. This course will teach students the fundamentals of product management, including product development, market research, and user experience design. Students will learn how to define product requirements, create product roadmaps, and launch new products.
Marketing Manager
A Marketing Manager interested in using artificial intelligence to improve marketing campaigns may find this Introduction to Large Language Models - Français course helpful. This course will provide a comprehensive overview of the field of marketing, including marketing strategy, market research, and digital marketing. Students will learn how to develop and execute marketing campaigns, and how to use data to measure their effectiveness.
Sales Manager
A Sales Manager who wants to learn how to use AI to improve their sales process may find this Introduction to Large Language Models - Français course helpful. This course will teach students the fundamentals of sales management, including sales strategy, sales process, and customer relationship management. Students will learn how to build and manage a sales team, and how to use data to improve their sales performance.
Customer Success Manager
For a Customer Success Manager looking to leverage data to improve customer satisfaction and retention, this Introduction to Large Language Models - Français course may be useful. This course will teach students the fundamentals of customer success management, including customer onboarding, customer support, and customer churn management. Students will learn how to build and manage a customer success team, and how to use data to improve their customer success rate.
Operations Manager
An Operations Manager who wants to improve the efficiency of their operations may find this Introduction to Large Language Models - Français course useful. This course will teach students the fundamentals of operations management, including process improvement, inventory management, and supply chain management. Students will learn how to design and implement operational processes, and how to use data to improve their operational performance.
Project Manager
A Project Manager interested in using AI to improve project outcomes could benefit from this Introduction to Large Language Models - Français course. This course will teach students the fundamentals of project management, including project planning, project execution, and project control. Students will learn how to define project scope, develop project plans, and manage project risks.
Risk Manager
For a Risk Manager looking to use AI to identify and manage risks, this Introduction to Large Language Models - Français course may be helpful. This course will teach students the fundamentals of risk management, including risk identification, risk assessment, and risk mitigation. Students will learn how to develop and implement risk management plans, and how to use data to improve their risk management practices.
Compliance Manager
A Compliance Manager who wants to use AI to ensure compliance with regulations may find this Introduction to Large Language Models - Français course useful. This course will teach students the fundamentals of compliance management, including compliance auditing, compliance monitoring, and compliance reporting. Students will learn how to develop and implement compliance programs, and how to use data to improve their compliance performance.
Quality Assurance Manager
For a Quality Assurance Manager interested in using AI to improve the quality of their products or services, this Introduction to Large Language Models - Français course may be useful. This course will teach students the fundamentals of quality assurance, including quality planning, quality control, and quality improvement. Students will learn how to develop and implement quality assurance programs, and how to use data to improve their quality assurance practices.
Information Security Manager
An Information Security Manager who wants to use AI to improve the security of their organization's data and systems may find this Introduction to Large Language Models - Français course useful. This course will teach students the fundamentals of information security, including information security risk assessment, information security controls, and information security incident management. Students will learn how to develop and implement information security programs, and how to use data to improve their information security practices.

Reading list

We've selected 11 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 - Français.
Provides a comprehensive overview of language models, from basic concepts to advanced techniques. Useful for gaining a deeper understanding of the theoretical foundations of LLM.
Provides a comprehensive overview of information theory, inference, and learning algorithms, which are fundamental concepts for understanding and developing machine learning models.
Provides a comprehensive overview of deep learning with Python. Useful for gaining a deeper understanding of the underlying algorithms used in LLM.
Provides a comprehensive overview of the field of natural language processing, covering topics such as language modeling, machine translation, and question answering.
Provides a comprehensive overview of reinforcement learning, which type of machine learning that allows agents to learn how to behave in an environment by interacting with it.
Offers practical guidance on building and deploying NLP applications. Useful for learners who want to apply their knowledge of LLM in real-world projects.
Provides a comprehensive overview of statistical methods for machine learning, covering topics such as supervised learning, unsupervised learning, and reinforcement learning.
Covers the fundamentals of speech and language processing, including natural language understanding and generation. Useful for gaining a broader perspective on NLP and its applications.
Provides a comprehensive overview of NLP, including its history, techniques, and applications. Useful for gaining a broader perspective on NLP and its applications.
Provides a comprehensive overview of the mathematical foundations of machine learning, covering topics such as probability, statistics, and optimization.
Provides a clear and concise introduction to linear algebra, which fundamental mathematical tool for many areas of science and engineering, including machine learning and natural language processing.

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