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 Duration 21 hours

Course Outline

Fundamentals of Sentiment Analysis in Large Language Models

  • Core principles and applications of sentiment analysis for government operations
  • Strategic challenges and operational opportunities in sentiment analysis
  • Overview of Large Language Models and their technical capabilities

Large Language Models and Natural Language Interpretation

  • Structural analysis of Large Language Model architectures
  • Interpreting contextual nuance and sentiment through LLMs
  • Procedures for preprocessing data for sentiment analysis

Developing Sentiment Analysis Models with Large Language Models

  • Training methodologies for LLMs in sentiment analysis contexts
  • Optimizing models for specific sectoral domains
  • Practical application exercises in model development

Social Media Analysis Using Large Language Models

  • Protocols for collecting social media data for analysis
  • Implementing real-time sentiment tracking on public platforms
  • Examination of case studies in social sentiment analysis

Sentiment Analysis in Public and Customer Feedback

  • Deriving strategic insights from reviews and survey responses
  • Improving service delivery through sentiment analysis
  • Applied workshop on feedback analysis methodologies

Advanced Applications in Sentiment Analysis

  • Techniques for addressing sarcasm, irony, and complex emotional states
  • Cross-language sentiment analysis capabilities
  • Future developments in sentiment analysis with LLMs for government use
  • Ethical Frameworks and Bias Mitigation

    • Ethical implications of deploying sentiment analysis systems
    • Identifying and mitigating algorithmic bias in models
    • Standards for the responsible use of sentiment analysis

    Project Implementation and Evaluation

    • Analyzing sentiment from a selected dataset
    • Peer review and collaborative discussion processes
    • Final performance assessment and feedback mechanisms

    Conclusions and Strategic Next Steps

    Requirements

    • Demonstrated understanding of foundational machine learning concepts
    • Practical experience with text data preprocessing and analytical techniques
    • Proficiency in Python programming languages

    Target Audience

    • Data scientists and policy analysts
    • Communications and marketing professionals
    • Program and project managers

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