Transform your financial services expertise with our 2-Day Prompt Engineering and NLP course, designed for professionals to master advanced language models and enhance financial decision-making processes.
Master core prompting techniques for financial services.
Implement advanced prompting patterns in financial workflows.
Evaluate and test prompt effectiveness and ethical use.
Apply multimodal prompting including text and image integration.
This course focuses on imparting the essential and advanced skills required for mastering prompt engineering and natural language processing, specifically tailored for financial services applications. Spread over two days, it covers core techniques, multimodal prompting, evaluation methods, and addresses ethical considerations in AI, empowering professionals to revolutionize their financial workflows.
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Introduction to Large Language Models
Writing Effective Prompts for LLMs
Define Prompt Parameters: Task/Inputs/Outputs/Constraints/Style
Precision Prompting for Financial Use Cases – Build prompts for transaction review and financial client education
The Iterative Nature of Prompting
Prompt Techniques – Chaining, Role Setting, Feedback
Zero-shot and Few-shot Prompting – When to use which
Implementing Zero-shot and Few-shot Techniques in Finance
Chain-of-Thought (CoT) Prompting
CoT Prompting – Financial logic scenarios
Tree-of-Thought (ToT) Prompting
ToT Prompting for Investment Risk Assessment
ReAct Prompting – Reasoning and Action for Financial Tools
ReAct Prompting – Interactive decision-making tasks
CoVe Prompting – Using Embeddings in Financial Contexts
Embedding-Driven Prompting – Leverage client context vectors
Common Prompting Patterns – Instructional, Conditional, Storytelling
Applying Prompting Patterns for Client Communication
Introduction to Multimodal Prompting
Text + Image Prompting – Use financial graphs and charts in prompts
Producing File Outputs (PDF/CSV Summaries)
Prompt Evaluation Tools and Metrics – Accuracy, Consistency, Relevance
A/B Testing Prompts for Financial Workflows
Ethical Prompting – Avoiding Bias and Ensuring Fairness
Navigating AI Ethics in Financial Applications
Final Prompting Review and Best Practices
Define Prompt Parameters: Task/Inputs/Outputs/Constraints/Style
Precision Prompting for Financial Use Cases – Build prompts for transaction review and financial client education
Prompt Techniques – Chaining, Role Setting, Feedback
Implementing Zero-shot and Few-shot Techniques in Finance
CoT Prompting – Financial logic scenarios
ToT Prompting for Investment Risk Assessment
ReAct Prompting – Interactive decision-making tasks
Embedding-Driven Prompting – Leverage client context vectors
Applying Prompting Patterns for Client Communication
Text + Image Prompting – Use financial graphs and charts in prompts
Producing File Outputs (PDF/CSV Summaries)
A/B Testing Prompts for Financial Workflows
Capstone Lab – Apply ToT, CoT, ReAct in a Financial Workflow Scenario
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Aaron Steele
Casey Pense
Chris Tsantiris
Javier Martin
Justin Gilley
Kathy Le
Kelson Smith
Oussama Azzam
Pascal Rodmacq
Randall Granier
Aaron Steele
Casey Pense
Chris Tsantiris
Javier Martin
Justin Gilley
Kathy Le
Kelson Smith
Oussama Azzam
Pascal Rodmacq
Randall Granier