AI 201 Advanced-Artificial-Intelligence Concepts

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Overview
Curriculum
  • 9 Sections
  • 43 Lessons
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Welcome
1 Lesson
  1. Welcome
Key AI Terminologies
6 Lessons
  1. Introduction
  2. AI Models
  3. Model Types
  4. Neural Networks
  5. Additional Terminologies
  6. Key Takeaways
Utilization of Generative AI
6 Lessons
  1. Introduction
  2. Chatbots and Virtual Assistants
  3. Content Generation
  4. Business Applications
  5. Agents and Automation
  6. Key Takeaways
Retrieval-Augmented Generation (RAG) and Related Concepts
6 Lessons
  1. Introduction
  2. Retrieval-Augmented Generation (RAG)
  3. Comparison with Traditional Models
  4. Other Related Concepts
  5. Practical Applications
  6. Key Takeaways
AI Agents and Agentic Architectures
6 Lessons
  1. Introduction
  2. AI Agents
  3. Agentic Architectures
  4. Interaction with Environments
  5. Use Cases
  6. Key Takeaways
The Future of AI and Compound Systems
6 Lessons
  1. Introduction
  2. Multi-Agent Systems
  3. Multi-Model Systems
  4. Compound Systems
  5. Future Trends
  6. Key Takeaways
Quantum Computing and Its Correlation with AI
6 Lessons
  1. Introduction
  2. Quantum Computing Basics
  3. Quantum AI
  4. Current Research and Developments
  5. Potential Applications
  6. Key Takeaways
Additional Advanced AI Concepts
5 Lessons
  1. Explainable AI (XAI)
  2. Ethical AI
  3. AI in Edge Computing
  4. Human-AI Collaboration
  5. Key Takeaways
Conclusion
1 Lesson
  1. Conclusion

This on-demand course is designed to help learners understand key artificial intelligence (AI) concepts, including popular terminologies, practical applications, and emerging trends in AI technologies. It is ideal for individuals who have a basic understanding of AI and want to deepen their knowledge in areas such as Generative AI, AI agents, AI models, and quantum computing. The course includes interactive elements, video lectures, and slides to guide you through each topic.

 

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