Multi-Agent AI Systems for Financial Services

Master the architecture of Multi-Agent AI for finance. You will move beyond simple chatbots to build specialized agent teams that collaborate on high-stakes workflows like OTC trading. Using Python and PydanticAI, you will learn to implement orchestration, intelligent routing, and persistent state management to create immutable audit trails. You will master the critical balance of blending non-deterministic AI reasoning with deterministic compliance logic. In the course project, "Agentic Alpha," you will architect a fully functional, autonomous trading system that analyzes markets, calculates risk, and enforces regulatory rules in real-time.

Course

Intermediate
14 hours
Updated: Jan 5, 2026

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Hands-on projects with expert feedback
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Program Certificates

Skills you'll learn

14 skills

Multi-Agent System Design
Agentic Integration
Multi-Agent State Management Concepts
Multi-Agent Systems
Multi-Agent State Coordination Concepts

Prerequisites

4 prerequisites

Prior to enrolling, you should have the following knowledge:

LLM Structured Outputs
REST APIs
Intermediate Python
Agent Tool Use

You will also need to be able to communicate fluently and professionally in written and spoken English.

Course Outline

14 lessons
1 project

Multi-Agent AI Systems for Financial Services

Introduction to Multi-Agent AI Systems for Financial Services
Learn about the course, prerequisites, and technical environment.
Designing Multi-Agent Architecture for Financial Services
Explore how specialized agents collaborate in a multi-agent AI architecture for hedge funds, focusing on data, strategy, risk, compliance, and trade execution flows.
Implementing Multi-Agent Architecture with Python for Financial Services
Learn to implement multi-agent architectures in Python for financial services using Pydantic AI, shared context, clear agent roles, and strict output structures for robust communication.
Orchestrating Agent Activities
Apply orchestration techniques to coordinate multiple agent actions and achieve complex workflows.
Implementing Agent Orchestration for Financial Services
Learn how to implement agent orchestration in financial services by combining deterministic flows with AI-powered decision making, using orchestration patterns and structured output models.
Routing and Data Flow in Agentic Systems
Configure routing mechanisms to manage data flow among agents in multi-agent systems.
Implementing Routing and Data Flow in Agentic Systems for Financial Services
Learn to implement routing strategies, agent pooling, and data flow orchestration for multi-agent financial systems using LLM and classic methods to balance loads and optimize message handling.
State Management in Multi-Agent Systems
Evaluate methods for tracking and updating agent state across multi-turn interactions.
Implementing State Management in Multi-Agent Systems for Financial Services
Learn to implement persistent, auditable state management in multi-agent trading systems using CSV files, ensuring consistent, reliable execution and separation of decision and action.
Multi-Agent Orchestration and State Coordination
Develop a coordinated multi-agent system that synchronizes states for coherent task execution.
Implementing Multi-Agent Orchestration and State Coordination for Financial Services
Learn to coordinate multiple specialist AI agents for financial trade processing using state management, conflict detection, and atomic transactions for robust multi-agent orchestration.
Multi-Agent Retrieval Augmented Generation
Extend RAG to multiple cooperating agents, each specialized in certain retrieval tasks.
Implementing Multi-Agent Retrieval Augmented Generation for Financial Services
Learn how to build a Multi-Agent Retrieval-Augmented Generation system for finance, coordinating specialized agents for comprehensive trading analysis and recommendations.

Project: Agentic Alpha
Build a multi-agent trading system. Coordinate specialized AIs to analyze markets, manage risk, and enforce compliance rules.

Program Instructors

2 instructors

Unlike typical professors, our instructors come from Fortune 500 and Global 2000 companies and have demonstrated leadership and expertise in their professions:

David Pazmino

Christopher Agostino

Founder and Research Scientist at NPC Worldwide

David Pazmino

Christopher Agostino

Founder and Research Scientist at NPC Worldwide

About this program

Learn to design multi-agent AI systems for finance. Build coordinated agents for portfolio analysis, risk, and trading systems.

Subscription · Monthly

Cancel Anytime
Unlimited access to hundreds of top-rated courses
Hands-on projects with expert feedback
Personalized career coaching and interview prep
Program Certificates

Multi-Agent AI Systems for Financial Services

Skills you'll learn

Prerequisites

Course Outline

Program Instructors

About this program

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