The course "Generative AI" provides an in-depth exploration of generative AI, focusing on both the theory and practical applications of transformers, large language models, and symbolic AI. By completing the course, learners will gain a comprehensive understanding of how these technologies work and how they can be integrated to solve complex problems and generate new content. Through real-world case studies, students will analyze the strengths and weaknesses of generative AI systems, preparing them for the challenges and opportunities they will face in AI leadership roles.
Generative AI
Ce cours fait partie de Spécialisation AI Strategy and Project Management
Instructeur : Ian McCulloh
Inclus avec
Expérience recommandée
Ce que vous apprendrez
Understand the theory and applications of generative AI, including transformers, large language models, and symbolic reasoning for content creation.
Explore how AI integrates with generative models to improve explainability, control, and responsible AI solutions in real-world applications.
Learn how to manage AI projects at scale, focusing on integrating generative and symbolic AI to address ethical considerations.
Compétences que vous acquerrez
- Catégorie : AI Project Management Strategies
- Catégorie : AI Vulnerabilities and Ethics
- Catégorie : Generative AI Methods
- Catégorie : Transformers and Large Language Models
- Catégorie : Symbolic AI Integration
Détails à connaître
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décembre 2024
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Il y a 3 modules dans ce cours
This course explores the theory and application of generative AI, focusing on the differences between stochastic AI, expert systems, and symbolic AI. You will learn how symbolic AI can be generative and how both stochastic and symbolic approaches can be integrated. Emphasis is placed on creating holistic, responsible AI solutions. Through practical examples, you will gain a deep understanding of AI's capabilities and ethical considerations.
Inclus
1 lecture1 plugin
This module explores the fundamentals and applications of Large Language Models (LLMs) and Transformers. It covers the foundations, capabilities, and fine-tuning of LLMs like ChatGPT, as well as their use in image generation. The module also addresses challenges such as hallucinations, vulnerabilities, and model competence, providing a comprehensive understanding of LLMs and their real-world implications.
Inclus
9 vidéos2 lectures3 devoirs
This module explores the intersection of symbolic and generative AI, focusing on how symbolic AI informs and enhances generative processes. Building on prior knowledge of generative AI, it integrates symbolic reasoning with stochastic models to create responsible AI solutions. Key topics include symbolic AI, formal methods, relational calculus, and data integration, essential for enabling systems to generate insights in diverse environments. The module emphasizes how combining rule-based reasoning with generative AI fosters explainable, transparent systems that align with ethical and regulatory standards.
Inclus
13 vidéos3 lectures3 devoirs
Instructeur
Offert par
Recommandé si vous êtes intéressé(e) par Machine Learning
University of Michigan
Google Cloud
Google Cloud
Fractal Analytics
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