Certified Prompt Engineer For Finance & Banking (CpeFb)

Certified Prompt Engineer For Finance & Banking (Cpe-Fb)
Published 2/2025
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz

Unlock AI’s Potential in Finance: A Foundational Course for Prompt Engineering Excellence

What you’ll learn

Master foundational AI technologies in finance

Understand AI’s transformative role in banking

Gain insights into natural language processing

Learn to design effective AI prompts for finance

Address ethical considerations in AI deployment

Explore large language models and tokenization

Fine-tune AI models for financial applications

Develop strategies to handle AI bias and limitations

Design prompts for fraud detection and prevention

Create AI prompts for risk assessment and analysis

Leverage AI for personalized financial advisory services

Apply advanced techniques in prompt engineering

Understand AI governance and compliance requirements

Evaluate and improve AI-generated financial responses

Explore future trends in AI prompt engineering

Integrate AI with emerging technologies in finance

Requirements

An analytical mindset – The ability to assess and interpret AI-generated financial insights with precision.

A commitment to ethical responsibility – An understanding of the importance of compliance and responsible AI use in finance.

Attention to detail – The ability to craft accurate AI prompts and monitor AI-driven financial processes.

A willingness to learn – An openness to exploring new AI techniques and adapting to evolving financial technologies.

Description

Overview

Section 1: Course Preparation

Lecture 1 Course Preparation

Section 2: Introduction to AI and Prompt Engineering

Lecture 2 Section Introduction

Lecture 3 Understanding AI in Finance & Banking

Lecture 4 Basics of Natural Language Processing (NLP)

Lecture 5 Fundamentals of Prompt Engineering

Lecture 6 Ethical Considerations in AI Prompt Usage

Lecture 7 Role of AI in Modern Financial Services

Lecture 8 Section Summary

Section 3: AI Models and Language Processing

Lecture 9 Section Introduction

Lecture 10 Overview of Large Language Models (LLMs)

Lecture 11 Tokenization and Context Awareness in Finance Prompts

Lecture 12 Fine-Tuning AI Models for Financial Applications

Lecture 13 Handling Bias and Limitations in AI Models

Lecture 14 Optimizing AI Responses for Financial Accuracy

Lecture 15 Section Summary

Section 4: Designing Effective Prompts for Fraud Detection

Lecture 16 Section Introduction

Lecture 17 Understanding Financial Fraud Types & AI’s Role

Lecture 18 Structuring Prompts for Anomaly Detection

Lecture 19 AI-Powered Transaction Monitoring & Red Flags
Lecture 20 Prompt Optimization for Fraud Prevention Systems

Lecture 21 Leveraging AI for Fraud Trend Analysis

Lecture 22 Section Summary

Section 5: Risk Assessment Using AI Prompts

Lecture 23 Section Introduction

Lecture 24 Fundamentals of Financial Risk & AI Integration

Lecture 25 Creating AI Prompts for Risk Identification

Lecture 26 AI-Powered Credit Risk and Scoring Models

Lecture 27 Enhancing Due Diligence with AI-Driven Prompts

Lecture 28 Addressing Uncertainty and Bias in Risk Analysis

Lecture 29 Section Summary

Section 6: AI Prompt Engineering for Financial Advisory Services

Lecture 30 Section Introduction

Lecture 31 AI in Personalized Financial Advice

Lecture 32 Designing Prompts for Investment Strategies

Lecture 33 AI for Portfolio Optimization and Wealth Management

Lecture 34 Regulatory Compliance in AI-Based Advisory Services

Lecture 35 Improving AI-Powered Customer Engagement

Lecture 36 Section Summary

Section 7: Advanced Techniques in Prompt Engineering

Lecture 37 Section Introduction

Lecture 38 Chain of Thought (CoT) Prompting for Financial Analysis

Lecture 39 Few-Shot and Zero-Shot Prompting in Finance

Lecture 40 Multi-Turn Conversations for AI-Driven Finance Queries

Lecture 41 Dynamic Prompting for Real-Time Financial Decision-Making

Lecture 42 Troubleshooting AI Prompt Failures in Banking

Lecture 43 Section Summary

Section 8: AI Governance, Security, and Compliance

Lecture 44 Section Introduction

Lecture 45 AI Ethics and Governance in Banking & Finance

Lecture 46 Regulatory Requirements for AI Implementation

Lecture 47 Data Privacy & Security Considerations in AI Prompts

Lecture 48 Ensuring Explainability & Transparency in AI Responses

Lecture 49 Managing AI Risks in Financial Institutions

Lecture 50 Section Summary

Section 9: Evaluating and Improving AI-Generated Responses

Lecture 51 Section Introduction

Lecture 52 Metrics for Assessing AI Prompt Effectiveness

Lecture 53 Improving Accuracy and Precision in Financial AI Prompts

Lecture 54 Strategies for Reducing AI Hallucinations in Finance

Lecture 55 Human-AI Collaboration for Financial Decision-Making

Lecture 56 Continuous Learning & Updating AI Models

Lecture 57 Section Summary

Section 10: Automation and AI-Driven Decision Support

Lecture 58 Section Introduction

Lecture 59 AI-Powered Process Automation in Banking

Lecture 60 Using AI Prompts for Regulatory Reporting

Lecture 61 AI for Automated Loan Underwriting and Approvals

Lecture 62 Enhancing Customer Service with AI Chatbots

Lecture 63 AI-Driven Predictive Analytics for Financial Trends

Lecture 64 Section Summary

Section 11: Future Trends and Emerging Technologies in AI Prompt Engineering

Lecture 65 Section Introduction

Lecture 66 The Future of AI in Finance & Banking

Lecture 68 AI-Driven Financial Market Predictions

Lecture 69 The Role of Quantum Computing in Financial AI

Lecture 70 Ethical AI and the Evolution of Prompt Engineering

Lecture 71 Section Summary

Section 12: Course Summary

Lecture 72 Conclusion

Financial analysts seeking to integrate AI into their analysis processes,Banking professionals aiming to enhance fraud detection methods,Risk management specialists looking to optimize AI-driven strategies,IT experts in finance wanting to master AI prompt engineering,Compliance officers needing to understand AI regulatory frameworks,Financial advisors interested in AI-powered personalized services,Data scientists in finance aiming to advance AI modeling skills,Executives in finance seeking to lead AI innovations in their firms