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Course Outline

Introduction to AI

  • Overview of AI and its transformative impact across different industries.
  • Understanding the foundational principles of machine learning and deep learning.
  • Exploring the evolution of AI technologies and their current operational capabilities.

Introduction to Generative AI and Large Language Models (LLM)

  • Understanding the principles and applications of generative AI.
  • Examining the architecture and capabilities of ChatGPT.
  • Addressing privacy concerns and data security issues.
  • Techniques for Prompt Engineering.

Foundations of Retrieval Augmented Generation (RAG)

  • The concept of RAG and its role in enhancing generative models.
  • Integrating retrieval mechanisms into generative models for improved context comprehension.
  • Workshop: Implementing a basic RAG model for information retrieval.

GPT + RAG for Insights from Unstructured Data

  • Methods for extracting valuable insights from unstructured data using GPT and RAG.
  • Case study: Analysing textual data to derive business intelligence.

GPT for Insights from Structured Data

  • Applying GPT models to the analysis of structured datasets.
  • Techniques for converting structured data into formats compatible with GPT.

AI Tools and Software

  • ChatGPT
  • Claude
  • Copilot
  • LlamaIndex
  • LangChain
 7 Hours

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