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Generative AI Foundational Concepts - Part 2

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Introduction to Generative AI

In the first part of our series on generative AI, we explored foundational concepts and basic applications. In this second part, we will delve deeper into advanced models, multimodal capabilities, and practical applications of generative AI.

Key topics to understand in Generative AI - Part 2

  • Multimodal Models
  • Diffusion Models
  • Making an app using Supervised Learning VS using Generative AI
  • How to improve performance of Generative AI models
    • Better prompting
    • Retrieval Augmented Generation (RAG)
    • Fine-tuning models
    • Pre-training models
  • How to choose suitable LLM for your applications
    • Choose by model size
    • Open-source or Closed-source
  • What is instruction tuning
  • What is Reinforcement Learning from Human Feedback (RLHF)

I highly recommend the Generative AI For Everyone course on Coursera. This course is designed to provide a comprehensive introduction to AI, covering the essential concepts and technologies that form the backbone of modern AI applications. It's perfect for beginners and offers a solid foundation before moving on to more specialized topics.

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