Finance with AI: AI Tools & Real Use Cases (Beginner to Pro)

Rookie Guru – Finance + AI Course Curriculum

A complete beginner-to-advanced journey into AI-powered finance. This course helps learners understand how artificial intelligence is transforming finance, accounting, forecasting, and compliance processes.

Introductory Chapter: Understanding Meta AI in Finance

• What is Meta AI?

• Which LLM version is used

• AI’s capabilities and limitations in finance

• Basics of prompt engineering (zero/one/few-shot)

• Responsible usage disclaimers

Chapter 1: The Future of AI in Finance & Accounting

• Evolution of AI in finance and accounting

• Impact of AI on financial operations

• Introduction to prompt engineering techniques

Chapter 2: AI in Financial Planning & Forecasting

• Budgeting and forecasting with AI tools

• Personal vs corporate terminology

• AI-assisted financial modeling

• Lab 1: Prompting AI for Finance-Specific Excel Tasks (Coming soon)

• Lab 2: AI-Assisted Forecasting in Excel (Coming soon)

• Lab 3: Cleaning Financial Data with ChatGPT (Coming soon)

Chapter 3: AI for Bookkeeping & Transaction Management

• Automating bookkeeping workflows with AI

• Tangible vs intangible assets explained

• Balance sheet walkthrough (Meta 10-K example)

• Tally Workflow Demo with AI Concepts (Coming soon)

• QuickBooks + AI Integration Concepts (Coming soon)

Chapter 4: AI for Accounting & Financial Compliance

• Income Statement preparation

• Balance Sheet analysis

• Cash Flow Statement preparation

• Compliance workflows (corporate and personal taxation)

Chapter 5: AI in Auditing & Fraud Detection

• AI-driven audit processes

• Fraud detection and anomaly identification

• Case workflows

Chapter 6: AI for Personal & Business Finance

• Personal budgeting with AI

• Debt management and credit scoring

• Business finance automation

• Data privacy and AI limitations

Chapter 7: AI in Business Valuation & Investment Strategy

• Business valuation metrics

• Profitability ratios

• Liquidity ratios

• AI-based investment analysis

Chapter 8: AI for Financial Research & Data Retrieval

• Summarizing and extracting financial data

• EBIT and EBITDA explained with examples

• Case study: Apple Inc. financials

• AI for qualitative and quantitative research

Chapter 9: AI for Expense Optimization & Cost Reduction

• Identifying cost inefficiencies

• AI-driven strategies for cost cutting

• Efficiency-focused financial analysis

Chapter 10: AI for Business Valuation Techniques

• Discounted Cash Flow (DCF)

• Relative valuation

• Precedent transactions

• Multiples (EV/EBITDA, P/E, etc.)

Chapter 11: AI Risk & Data Security

• Why AI outputs may be unreliable

• Risks of sharing sensitive data

• Data security best practices

• Risks with vector databases and embedded memory

Chapter 12: AI Ethics & Governance in Finance

• Fairness, bias, and transparency in AI

• Explainable AI in finance

• Current and emerging regulatory frameworks

• Governance and risk management standards

Chapter 13: AI for Derivatives & Risk Management

• Introduction to derivatives (futures, options, swaps)

• Portfolio hedging with AI

• Greeks analysis and volatility modeling

• Stress testing and scenario modeling with AI

Capstone Project (Coming soon): AI-Powered Budgeting for a Retail Firm

• Project brief and scenario setup

• Instructor walkthrough (AI + Excel Forecasting)

• Submission tips and portfolio guidance

• Retail dataset, Prompt Guide, and Excel Template

Career Mapping Resource (Coming soon)

• Career roles and skills mapping (PDF)

• Resume bullet points and LinkedIn examples

• Optional video on showcasing skills in interviews

Bonus Module (Coming soon): AI Tools in Action

• Tome – AI for financial presentations

• SaasAnt – QuickBooks automation walkthrough

• Syft Analytics – AI dashboards and reporting

High-Quality Promo Video (Coming soon)

• Hook and introduction

• Course outcomes and skills gained

• Target roles and learner impact

• Call to action to enroll

Course Wrap-Up

• Review of key concepts

• Next steps for applying AI in finance

• Guidance on projects and showcasing skills