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Google Cloud Training

L'intelligence artificielle (IA) et le machine learning (ML) représentent une évolution importante de l'informatique et transforment rapidement un grand nombre de secteurs. Le cours ""Innovating with Google Cloud Artificial Intelligence"" explore comment les organisations peuvent utiliser l'IA et le ML pour repenser leurs processus métier.

Ce cours fait partie du parcours de formation Cloud Digital Leader. Il vise à aider les participants à évoluer dans leur poste et à bâtir l'avenir de leur entreprise.

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What's inside

Syllabus

Présentation du cours
Vous allez découvrir les objectifs du cours et chaque section sera présentée.
Principes de base de l'IA et du ML
L'intelligence artificielle et le machine learning peuvent offrir de nombreux avantages aux entreprises. Toutefois, il est important de comprendre leurs principes de base avant de commencer à les implémenter. Dans cette section du cours, nous allons découvrir un grand nombre de ces principes.
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Solutions d'IA et de ML de Google Cloud
Dans cette section du cours, nous allons découvrir quatre options pour créer des modèles de ML avec Google Cloud : BigQuery ML, les API pré-entraînées, AutoML et l'entraînement personnalisé.
Résumé du cours
Le cours se termine par un récapitulatif des principaux points abordés dans chaque section et une présentation des étapes à suivre pour continuer votre apprentissage.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Développe les compétences fondamentales de l'IA et du ML pour les leaders du numérique
Fait partie du parcours de formation Cloud Digital Leader, conçu pour aider les participants à progresser dans leur carrière et à bâtir l'avenir de leur entreprise
Adopte une approche pratique, avec des exercices et des études de cas pour une meilleure compréhension
Présenté par Google Cloud Training, qui possède une solide réputation dans le domaine de l'IA et du ML
Axé sur l'innovation, aidant les entreprises à repenser leurs processus métier à l'aide de l'IA et du ML
Couvre les principes de base de l'IA et du ML, les solutions de Google Cloud et le développement de modèles de ML

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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 Innovating with GC Artificial Intelligence - Français with these activities:
Suivre des tutoriels sur les solutions d'IA et de ML de Google Cloud
Découvrez les différentes options proposées par Google Cloud pour créer des modèles de ML et choisissez celle qui convient le mieux à vos besoins.
Browse courses on BigQuery ML
Show steps
  • Suivre le tutoriel sur BigQuery ML
  • Explorer la documentation sur les API pré-entraînées
  • Créer un modèle AutoML
  • Développer un modèle d'entraînement personnalisé
Lire "Intelligence artificielle : une approche moderne" par Stuart Russell et Peter Norvig
Complétez votre apprentissage avec un texte reconnu sur l'IA et le ML pour approfondir votre compréhension et élargir votre perspective.
Show steps
  • Lire les chapitres pertinents du livre
  • Souligner et annoter les passages clés
  • Résumer les concepts principaux dans vos propres mots
Show all two activities

Career center

Learners who complete Innovating with GC Artificial Intelligence - Français will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineers are responsible for developing and implementing machine learning models. They work with data scientists to identify and gather the necessary data, and then use their expertise in machine learning algorithms to build models that can make predictions or classifications. This course can help Machine Learning Engineers by providing them with a foundation in the principles of AI and ML, as well as the tools and techniques needed to build and implement ML models in the cloud.
Data Scientist
Data Scientists use their knowledge of statistics, mathematics, and computer science to extract insights from data. They work with businesses to identify problems that can be solved using data, and then develop and implement solutions. This course can help Data Scientists by providing them with a foundation in the principles of AI and ML, as well as the tools and techniques needed to build and implement ML models in the cloud.
Software Engineer
Software Engineers are responsible for designing, developing, and maintaining software applications. They work with businesses to identify needs and develop solutions that meet those needs. This course can help Software Engineers by providing them with a foundation in the principles of AI and ML, as well as the tools and techniques needed to build and implement ML models in the cloud.
Business Analyst
Business Analysts work with businesses to identify and solve problems. They use their knowledge of business processes and data to develop solutions that improve efficiency and profitability. This course can help Business Analysts by providing them with a foundation in the principles of AI and ML, as well as the tools and techniques needed to build and implement ML models in the cloud.
Project Manager
Project Managers are responsible for planning, executing, and closing projects. They work with teams to ensure that projects are completed on time, within budget, and to the required quality standards. This course can help Project Managers by providing them with a foundation in the principles of AI and ML, as well as the tools and techniques needed to build and implement ML models in the cloud.
Data Architect
Data Architects are responsible for designing and building data systems. They work with businesses to identify data needs and develop systems that can store, process, and analyze data. This course can help Data Architects by providing them with a foundation in the principles of AI and ML, as well as the tools and techniques needed to build and implement ML models in the cloud.
Cloud Architect
Cloud Architects are responsible for designing and building cloud computing solutions. They work with businesses to identify cloud needs and develop solutions that meet those needs. This course can help Cloud Architects by providing them with a foundation in the principles of AI and ML, as well as the tools and techniques needed to build and implement ML models in the cloud.
Data Engineer
Data Engineers are responsible for building and maintaining data pipelines. They work with businesses to identify data needs and develop pipelines that can collect, store, and process data. This course can help Data Engineers by providing them with a foundation in the principles of AI and ML, as well as the tools and techniques needed to build and implement ML models in the cloud.
Machine Learning Scientist
Machine Learning Scientists are responsible for researching and developing new machine learning algorithms. They work with businesses to identify problems that can be solved using machine learning, and then develop and implement new algorithms to solve those problems. This course can help Machine Learning Scientists by providing them with a foundation in the principles of AI and ML, as well as the tools and techniques needed to build and implement ML models in the cloud.
AI Researcher
AI Researchers are responsible for researching and developing new AI technologies. They work with businesses to identify problems that can be solved using AI, and then develop and implement new technologies to solve those problems. This course can help AI Researchers by providing them with a foundation in the principles of AI and ML, as well as the tools and techniques needed to build and implement ML models in the cloud.
Computer Vision Engineer
Computer Vision Engineers are responsible for developing and implementing computer vision solutions. They work with businesses to identify problems that can be solved using computer vision, and then develop and implement solutions that use computer vision to solve those problems. This course can help Computer Vision Engineers by providing them with a foundation in the principles of AI and ML, as well as the tools and techniques needed to build and implement ML models in the cloud.
Natural Language Processing Engineer
Natural Language Processing Engineers are responsible for developing and implementing natural language processing solutions. They work with businesses to identify problems that can be solved using natural language processing, and then develop and implement solutions that use natural language processing to solve those problems. This course can help Natural Language Processing Engineers by providing them with a foundation in the principles of AI and ML, as well as the tools and techniques needed to build and implement ML models in the cloud.
Speech Recognition Engineer
Speech Recognition Engineers are responsible for developing and implementing speech recognition solutions. They work with businesses to identify problems that can be solved using speech recognition, and then develop and implement solutions that use speech recognition to solve those problems. This course can help Speech Recognition Engineers by providing them with a foundation in the principles of AI and ML, as well as the tools and techniques needed to build and implement ML models in the cloud.
Robotics Engineer
Robotics Engineers are responsible for designing, developing, and implementing robotic solutions. They work with businesses to identify problems that can be solved using robotics, and then develop and implement solutions that use robotics to solve those problems. This course may be helpful to Robotics Engineers by providing them with a foundation in the principles of AI and ML, as well as the tools and techniques needed to build and implement ML models in the cloud.
AI Product Manager
AI Product Managers are responsible for planning, developing, and marketing AI products. They work with businesses to identify product needs and develop products that meet those needs. This course may be helpful to AI Product Managers by providing them with a foundation in the principles of AI and ML, as well as the tools and techniques needed to build and implement ML models in the cloud.

Reading list

We've selected eight 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 Innovating with GC Artificial Intelligence - Français.
Traduction française de l'ouvrage de référence sur l'intelligence artificielle, offrant une vue d'ensemble complète du domaine.
Traduction française de l'ouvrage de référence sur le deep learning, offrant une introduction complète à cette technique avancée d'apprentissage automatique.
Provides an introduction to reinforcement learning, a type of machine learning that enables agents to learn how to behave in an environment.
Provides a practical guide to natural language processing, a field of artificial intelligence that deals with understanding and generating human language.
Provides a comprehensive introduction to computer vision, a field of artificial intelligence that deals with understanding and generating images.
Provides a comprehensive introduction to probabilistic graphical models, a powerful tool for representing and reasoning about complex systems.
Provides a comprehensive introduction to information theory, inference, and learning algorithms, which are fundamental to artificial intelligence.

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