Course Outline

Introduction to Prompt Engineering in Finance

  • Understanding prompt engineering and AI models
  • Applications of AI-driven prompts in financial analysis
  • Overview of AI tools and APIs for finance

Using AI for Financial Forecasting

  • Generating financial projections using AI prompts
  • Analyzing historical data for trend predictions
  • Enhancing accuracy through prompt optimization

Market Sentiment Analysis with AI

  • Extracting insights from financial news and reports
  • Using NLP-powered prompts for sentiment classification
  • Integrating AI-based sentiment analysis with financial models

Automating Financial Reporting

  • Generating financial summaries using AI
  • Automating data extraction from reports
  • Ensuring consistency and compliance in AI-generated reports

Risk Assessment and Fraud Detection

  • Developing AI-driven risk assessment models
  • Optimizing AI prompts for fraud detection
  • Case studies on AI-powered financial risk management

Enhancing Decision-Making with AI

  • Leveraging AI for investment strategy optimization
  • AI-driven scenario analysis and stress testing
  • Best practices for AI-assisted financial decision-making

Ethical and Compliance Considerations in AI-Driven Finance

  • Ensuring ethical use of AI in financial services
  • AI bias and its impact on financial decision-making
  • Regulatory considerations and AI compliance frameworks

Hands-On Labs and Real-World Applications

  • Building financial forecast models using AI prompts
  • Developing an AI-driven risk assessment tool
  • Automating market sentiment analysis

Summary and Next Steps

Requirements

  • Basic knowledge of finance and financial analysis
  • Experience with data analytics and financial modeling
  • Familiarity with AI and machine learning concepts (recommended)

Audience

  • Financial analysts
  • Risk managers
  • Fintech developers
 14 Hours

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