LLMs and AI Agents: Transforming Unstructured Data

Overview

Discover how LLMs, GPT models, and AI agents transform unstructured data into actionable insights, exploring OCR, NLP, and agentic workflows that reshape document intelligence.

Syllabus

• Introduction to LLMs and AI Agents
Overview of Large Language Models (LLMs)
The evolution and impact of AI agents
• Unstructured Data: Challenges and Opportunities
Understanding unstructured data
Potential applications and sectors
• Optical Character Recognition (OCR) Techniques
Basics of OCR technology
Tools and libraries for OCR
Integrating OCR in AI workflows
• Natural Language Processing (NLP) Fundamentals
Key NLP concepts and techniques
Text pre-processing and tokenization
Named entity recognition and sentiment analysis
• Large Language Models in Action
Overview of GPT models and capabilities
Fine-tuning and customizing LLMs
Case studies of LLMs processing unstructured data
• AI Agents and Agentic Workflows
Introduction to autonomous agents
Designing workflows with AI agents
Automation of decision-making processes
• Transforming Unstructured Data into Insights
Strategies for extracting actionable insights
Data visualization and reporting techniques
Case studies and industry applications
• Integration and Implementation
Integrating LLMs and AI agents in existing systems
Scalability and infrastructure considerations
• Ethical and Privacy Considerations
Data privacy in AI applications
Ethical implications of using AI agents
• Capstone Project
Developing a solution to transform unstructured data using LLMs and AI agents
Presentation and peer review of projects

Subjects

Computer Science