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Agentic AI Fundamentals: AI Agents, APIs, and Workflows
Rating: 4.7 out of 5(6 ratings)
421 students

Agentic AI Fundamentals: AI Agents, APIs, and Workflows

Learn how to build AI agents with memory, APIs, multi-agent systems, and real-world finance workflows using OpenAI tools
Created byExcel Mojo
Last updated 5/2026
English

What you'll learn

  • Understand the fundamentals of Agentic AI and intelligent AI systems
  • Learn how AI agents process instructions, reason, and generate responses
  • Build stateless and stateful AI agents with memory and context awareness
  • Configure and use OpenAI APIs in real-world AI workflows
  • Integrate external tools and financial APIs into AI agents
  • Retrieve market data, financial ratios, filings, and news using AI systems
  • Develop custom financial data-fetching functions for AI workflows
  • Understand how multi-agent systems collaborate across research and analysis tasks
  • Define specialized AI agent roles such as researcher, analyst, and writer
  • Learn how AI agents are applied in finance and business workflows
  • Implement guardrails and validation techniques to reduce hallucinated outputs
  • Understand responsible AI principles, governance, and ethical AI usage
  • Build a strong foundation in practical AI automation and intelligent workflows

Course content

1 section18 lectures2h 45m total length
  • Course Introduction12:09

    Get an overview of Agentic AI, what you will build in this course, and how AI agents are used in real finance and business workflows.

  • Setting Up The Environment8:51

    Learn how to set up your development environment, required tools, and libraries needed to build and test agent-based AI systems.

  • Configuring OpenAI API6:56

    Understand how to configure the OpenAI API, manage API keys securely, and connect your environment to large language models.

  • First AI Agent8:56

    Build your first AI agent and understand how agents receive instructions, generate responses, and perform basic reasoning tasks.

  • Modify The Model And Test Agent9:28

    Learn how to change model parameters, experiment with prompts, and test agent behavior for accuracy and consistency.

  • Build A Stateless AI Agent6:16

    Create a stateless AI agent that processes each request independently, ideal for simple queries and one-time tasks.

  • Develop A Stateful AI Agent13:48

    Develop a stateful AI agent that maintains memory across interactions, enabling context-aware and multi-step reasoning.

  • Tool used in Financial Agents Overview and Goals7:00

    Explore common tools used in financial AI agents and understand how tools extend agent capabilities beyond text generation.

  • Share Your Learning Experience0:53
  • Integrate Yahoo Finance / YCharts / SEC Edgar APIs15:41

    Learn how to integrate real financial data sources so your agents can access market data, ratios, news, and filings.

  • Develop Custom Financial Data Fetch Functions10:42

    Build custom data-fetching functions that allow AI agents to retrieve financial metrics, news, and SEC filings reliably.

  • Test Tool-Enabled Agents with Real Financial Queries10:00

    Test your AI agents using real finance questions and evaluate how they fetch data, analyze results, and explain insights.

  • Overview and Objectives Multi-Agent Collaboration for Finance5:21

    Understand why multi-agent systems matter in finance and how different AI agents collaborate like real analyst teams.

  • Configure OpenAI API and Required Tools5:43

    Set up advanced configurations and tools required to support multi-agent workflows and collaborative AI systems.

  • Define Agents14:05

    Learn how to define specialized agent roles such as researcher, analyst, and writer, and assign responsibilities clearly.

  • Safe AI for Financial WorkflowsSafe AI for Financial Workflows10:40

    Understand safety principles, validation techniques, and best practices for using AI responsibly in financial workflows.

  • Build Guardrails to Prevent Fake or Fabricated Data11:16

    Implement guardrails and validation checks to prevent hallucinated numbers and ensure financial data accuracy.

  • Responsible AI in Finance7:40

    Learn the principles of responsible AI, governance, compliance, and ethical considerations when deploying AI in finance.

Requirements

  • No prior Agentic AI knowledge required
  • Access to ChatGPT
  • Basic familiarity with AI concepts is helpful but not necessary
  • Basic Python understanding is useful but not mandatory
  • A laptop or desktop for hands-on learning

Description

**This course contains the use of artificial intelligence.**

AI is evolving far beyond simple chatbots. Modern AI systems can reason, remember context, use external tools, retrieve data, and collaborate across workflows.

This Agentic AI fundamentals course is designed to help you understand the basics of Agentic AI. Moreover, it explains how intelligent AI agents are built for practical finance and business workflows.

Are you a student, analyst, finance professional, or someone curious about the future of AI systems?

If so, you’re in the right place. This course offers a structured and beginner-friendly introduction to building AI agents using modern tools and real-world workflows.

You’ll begin by understanding what Agentic AI is, how AI agents operate, and how businesses are increasingly using intelligent systems to automate tasks, retrieve information, analyze data, and support decision-making.

From there, you’ll learn how to configure OpenAI APIs, set up your development environment, and build your first AI agent capable of processing instructions, generating responses, and performing reasoning tasks.

The course then walks you through stateless and stateful AI agents, helping you understand how memory, context retention, and multi-step reasoning improve the capabilities of AI systems.

You’ll also learn how AI agents integrate with tools and APIs to access external data sources. The course includes practical integrations with financial data sources such as Yahoo Finance, YCharts, and SEC Edgar, allowing agents to retrieve financial data, ratios, filings, and market information dynamically.

In addition, you’ll explore multi-agent collaboration systems where specialized agents work together across research, analysis, and reporting workflows similar to real analyst teams.

The course also focuses on responsible AI implementation, including AI safety principles, hallucination prevention, validation techniques, and guardrails designed to improve the reliability of AI-generated outputs.

Rather than focusing only on theory, this course emphasizes practical workflows and real-world applications so you can understand how intelligent AI systems are being applied across finance, analytics, and business environments.

By the end of this course, you will understand how modern AI agents are structured, how they interact with tools and APIs, and how businesses are beginning to use Agentic AI systems in real workflows.


Skills You Will Gain

  • AI agent development

  • Agentic AI workflows

  • OpenAI API integration

  • Multi-agent system design

  • AI memory and context management

  • Tool-enabled AI systems

  • Financial data integration

  • AI workflow automation

  • Responsible AI implementation

  • AI validation and guardrail systems

  • Intelligent workflow design

  • Finance-focused AI workflows


How This Course Helps You

  • Understand how intelligent AI agents work

  • Learn practical AI workflows used in modern businesses

  • Gain exposure to finance-focused AI systems

  • Understand how AI agents interact with tools and data

  • Learn the foundations of multi-agent AI systems

  • Build future-ready AI workflow knowledge


What Makes This Course Different

  • Focus on practical AI agent workflows rather than only theoretical concepts

  • Learn how AI agents are applied in real finance and business environments

  • Build stateless and stateful AI agents with memory and reasoning capabilities

  • Integrate external tools and financial APIs into AI workflows

  • Understand multi-agent collaboration systems and specialized agent roles

  • Explore responsible AI practices, validation techniques, and hallucination prevention

  • Structured beginner-friendly approach to understanding Agentic AI systems

  • Hands-on exposure to real-world finance and analytics workflow examples


By the End of This Course, You Will Be Able To

  • Build AI agents with reasoning and memory capabilities

  • Integrate APIs and tools into AI workflows

  • Create multi-agent collaboration systems

  • Retrieve and analyze financial information using AI agents

  • Implement safer and more reliable AI workflows

  • Understand how businesses use Agentic AI systems


About the Course Director

This course is directed by Dheeraj Vaidya, Co-Founder of WallStreetMojo and ExcelMojo. He brings more than two decades of experience in finance education and professional training.

Over the years, he has trained more than 100,000 students and professionals across various industries and has worked with organizations including JPMorgan, CLSA, Bennett Coleman, and Adventity.

His background covers different areas such as financial analysis, valuation, investing, and the integration of AI into modern finance workflows and education.

Who this course is for:

  • Beginners interested in Agentic AI
  • Finance professionals exploring AI workflows
  • Analysts interested in intelligent automation systems
  • Students curious about modern AI applications
  • Professionals exploring AI agents and automation tools
  • Anyone interested in the future of AI-driven workflows