AI & AI Agents in Finance: Future-Proof Your Career in the Age of AI
Dr. Ryan Ahmed
Professor & AI Expert (510K+ Students)
Master AI in Finance: From Predictive Models to Autonomous AI Agents
AI is transforming every role in finance.
The industry is shifting from spreadsheets and manual processes to AI-native workflows, where intelligent agents analyze data, generate reports, and automate decisions at scale.
The problem: Most finance professionals are either ignoring AI or using it as a glorified chatbot. They lack the skills to build predictive models, automate workflows, and deploy AI agents that handle real finance tasks autonomously.
The solution: This bootcamp takes you from AI basics to building autonomous agent teams. You'll build real financial models, automate workflows, and deploy agents used by top institutions like Goldman Sachs, Citi, and NBIM.
What makes this bootcamp unique?
AI-Powered Financial Modeling: Build regression, classification, and clustering models for forecasting, credit risk, and segmentation.
Workflow Automation: Automate reconciliation, reporting, and scenario planning using Claude, Copilot, & Python.
Building Finance AI Agents: Design agents that connect to financial data, generate reports, and execute multi-step workflows.
Autonomous Agent Teams: Architect a team of specialized AI agents that collaborate on end-to-end finance operations.
What you’ll learn
Future-proof your finance career by mastering AI tools, predictive modeling, and autonomous agents that handle real finance workflows.
Use Claude and Copilot to automate reconciliation, invoice processing, and data extraction from financial documents.
Build prompt engineering techniques tailored for finance to get reliable, auditable, and repeatable outputs.
Automate month-end reporting workflows that generate KPI summaries, cash flow narratives, and executive-ready decks.
Build regression models for revenue forecasting, cash flow projections, and cost modeling using Python and AI.
Apply classification to automate credit risk scoring, fraud detection, and transaction categorization.
Use clustering for customer segmentation, portfolio grouping, and anomaly detection in financial datasets.
Build multi-scenario financial models with best, base, and worst case projections using AI-assisted analysis.
Run sensitivity and what-if simulations to stress-test assumptions across pricing, volume, FX, and inflation.
Use Claude and Python together to generate narrative explanations alongside every forecast and scenario output.
Generate CFO-ready commentary, variance analysis, and KPI dashboards directly from raw financial data.
Automate data pipelines that extract, clean, classify, and summarize financial information at scale.
Build reusable AI templates for recurring reports including P&L summaries, budget vs. actuals, and board decks.
Design AI agents with tools, memory, and guardrails that connect to financial data sources autonomously.
Use Model Context Protocol (MCP) to give agents secure access to market data, ERPs, and accounting platforms.
Implement compliance-ready patterns including audit trails, access controls, and human-in-the-loop safety.
Architect multi-agent systems with specialized roles: data analyst, compliance checker, and reporting agent.
Build coordination workflows where agents communicate, share context, and handle handoffs autonomously.
Deploy a capstone agent team that handles end-to-end finance operations from data ingestion to deliverables.
Learn directly from Ryan
Dr. Ryan Ahmed
Professor, AI expert, & YouTuber who has taught 500,000+ learners worldwide.
Who this course is for
Finance Professionals & Analysts wanting to automate workflows, build predictive models, and deploy AI agents for reporting and forecasting.
CFOs, Controllers & Finance Managers who want to lead AI adoption and deploy autonomous agents for reconciliation and decision support.
Data-Savvy Accountants & FP&A Teams who want to move from manual spreadsheets to AI-powered workflows that analyze and forecast at scale.
Course syllabus
Week 1
Mar
31
AI Foundations for Finance, Automate Workflows & Report Generation
AI in Finance: What's Changed in 2026 & Why It Matters
Hands-On with Claude & Copilot for Real Finance Tasks
Automating Reconciliation, Data Extraction & Report Generation
[Build] Assignment 1: Automate a Month-End Reporting Workflow
Apr
3
Office Hours & Q&A
Week 2
Apr
7
Predictive Modeling for Finance (Regression, Classification & Clustering)
Regression: Revenue Forecasting, Cash Flow Projections & Cost Modeling
Classification: Credit Risk Scoring, Fraud Detection & Transaction Categorizing
Clustering: Customer Segmentation, Portfolio Grouping & Anomaly Detection
[Build] Multi-Scenario Forecasting Model with Narrative Summary
Apr
10
Office Hours & Q&A
Schedule
Live sessions
4 hrs / week
Each week begins with a 3-hour live deep-dive where we design, build, and review production-grade agentic AI systems together. On Fridays, we hold a 1-hour live Q&A and office hours session focused on troubleshooting builds, reviewing architectures, and unblocking your capstone progress.
Tue, Mar 31
5:00 PM—8:00 PM (UTC)
Fri, Apr 3
5:00 PM—6:00 PM (UTC)
Tue, Apr 7
5:00 PM—8:00 PM (UTC)
Projects
4 hrs / week
You'll spend ~4 hours per week building real AI-powered finance systems end-to-end. Each week builds on the last, from workflow automation and predictive modeling to AI agents, MCP, and autonomous agent teams. By the end, you'll ship a portfolio-ready capstone that demonstrates AI-powered finance skills employers are hiring for in 2026.
Async content
2 hrs / week
You’ll spend ~2 hours per week on focused async content, including short videos, code walkthroughs, and architecture deep dives. This material is designed to front-load concepts and patterns so live sessions can ,focus on real-world design decisions and hands-on building. All sessions are recorded and available on-demand.
$999
USD