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Course Outline

Introduction to Prompt Engineering in Finance

  • Grasping prompt engineering and AI model mechanics
  • The role of AI-driven prompts in financial analysis
  • A look at AI tools and APIs relevant to finance

Applying AI for Financial Forecasting

  • Creating financial projections via AI prompts
  • Interpreting historical data to predict trends
  • Improving accuracy through prompt refinement

AI-Based Market Sentiment Analysis

  • Deriving insights from financial news and reports
  • Employing NLP-driven prompts for sentiment classification
  • Merging AI sentiment analysis into financial models

Automation in Financial Reporting

  • Producing financial summaries with AI
  • Automating the extraction of data from reports
  • Maintaining consistency and compliance in AI-generated reports

Risk Assessment and Fraud Detection

  • Building AI-driven risk assessment models
  • Refining AI prompts for fraud detection tasks
  • Examining case studies on AI-powered financial risk management

Enhancing AI-Aided Decision-Making

  • Using AI to optimise investment strategies
  • Conducting AI-driven scenario analysis and stress testing
  • Adopting best practices for AI-assisted financial decisions

Ethical and Compliance Dimensions in AI-Driven Finance

  • Ensuring the ethical deployment of AI in financial services
  • Analysing AI bias and its effect on financial decisions
  • Reviewing regulatory considerations and AI compliance frameworks

Hands-On Labs and Real-World Scenarios

  • Constructing financial forecast models with AI prompts
  • Developing an AI-driven risk assessment tool
  • Automating the analysis of market sentiment

Summary and Next Steps

Requirements

  • Foundational knowledge of finance and financial analysis
  • Practical experience with data analytics and financial modelling
  • Familiarity with AI and machine learning concepts (recommended)

Intended Audience

  • Financial analysts
  • Risk managers
  • Fintech developers
 14 Hours

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