AI Agents in Finance: Architectures, Patterns, and Reasoning Paradigms

Hanane Dupouy

$149.99

Video Oct 2025 50mins 1st Edition

Hanane Dupouy

$149.99

Video Oct 2025 50mins 1st Edition

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Key benefits

Explore how modular agents plan, act, and communicate
Understand how cognitive frameworks enable explainability and adaptiveness
Compare modern agent frameworks to choose the right one for your stack
Implement agents that can analyze markets, synthesize insights, and refine trading logic

Description

AI agents are redefining what’s possible in modern finance. In AI Agents in Finance, Hanane Dupouy takes you on a deep dive into the architectures, reasoning models, and orchestration frameworks powering this new wave of intelligent systems. You’ll discover how agentic AI differs from standard LLM pipelines—and why autonomous, goal-driven reasoning is key to the next generation of financial innovation. From ReAct to Self-Refine, and from CrewAI to LangChain, this course brings clarity to a fast-moving space—showing how agentic design patterns can be applied to real-world finance problems, from quantitative analysis to automated strategy generation.

Who is this book for?

AI engineers and data scientists in the finance domain Quantitative analysts exploring automation through AI agents Fintech developers looking to integrate agent-based intelligence Anyone aiming to understand the intersection of AI reasoning and financial decision-making

What you will learn

How agentic AI workflows differ from traditional LLM applications
The core reasoning paradigms—including ReAct, Self-Refine, and Tree of Thoughts
How to design coordinated multi-agent systems for financial domains
The fundamentals of OpenAI's Agents SDK, AutoGen, CrewAI, LlamaIndex, and LangChain
How to apply these frameworks to finance-specific use cases like fundamental analysis, portfolio insights, and strategic refinement

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