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Build Autonomous AI Agents From Scratch With Python
Rating: 4.5 out of 5(5,082 ratings)
16,215 students

Build Autonomous AI Agents From Scratch With Python

Step-by-step guide to develop Autonomous AI Agents from Scratch with Python and ReAct Prompting.
Created byHasan Aboul Hasan
Last updated 12/2024
English

What you'll learn

  • Understand what an AI Agent is and how it works.
  • Understand The ReAct Prompt
  • Build a Basic AI Agent (Step-by-Step)
  • Simplify AI Agents With SimplerLLM
  • Build an SEO Auditor AI Agent (Real Example)
  • Get all the Codes & Templates

Course content

1 section • 13 lectures • 55m total length

  • What is an AI Agent?3:08

    Combine a language model with tools and external functions to form an AI agent. It reasons, splits tasks, and uses right tool such as weather data or web to answer.

  • Getting Started1:16
  • Basic Setup4:46

    Set up a Python project by creating a virtual environment, installing the OpenAI package, and building a text-generation function using the OpenAI API, with environment variables.

  • LLM Limitation in Action1:54

    Explore how language models struggle with real-time data by testing GPT-3.5 and GPT-4 without external tools, and learn how to enable live data access with autonomous AI agents.

  • Hardcoded Agent!4:38

    Build a hard coded AI agent that calls a weather function and injects its result into the prompt to overcome model limitations. This function chaining previews autonomous agents.

  • Understanding ReAct Prompt6:24

    Learn how to automate AI agents with the react prompt, using a thought-action-action response loop and function calls like get weather to answer questions.

  • Adding Functions9:03

    Define available actions and teach the model to return a json with function name and parameters, automatically calling the weather function for a city and looping to a final answer.

  • The Loop in Action!2:11

    Explore the loop of thought, action, and response to enable a model to remember the conversation, call extracted functions, and nest code inside a loop for a memory-enabled AI agent.

  • Our Final AI Agent6:59

    Finish building an ai agent by implementing a multi-turn loop that uses a messages-based conversation and weather function results to update context.

  • The Prompt3:17

    Design and compare system and react prompts to control an AI agent, favoring JSON responses over regular expressions for function calls, and tailor prompts for specific use cases like weather.

  • Using SimplerLLM3:11

    Learn how simpler LM simplifies building AI agents in Python by using a single LM instance with OpenAI, Gemini, or Anthropic providers, installable via pip, and paired with JSON tools.

  • AI SEO Auditor Agent8:13

    Build an ai editor agent in Python that can read web pages, generate a detailed seo audit, and answer questions like image count or optimization strategies.

  • What's Next?0:54

    practice building your own ai agent from scratch with Python and React Prompt, download the code, and tweak it to customize your agent; join the community for monthly projects.

Requirements

  • Basic to Intermediate Python Programming
  • Core concepts of prompt engineering

Description

Welcome to "Build AI Agents From Scratch with Python," a course designed for individuals eager to dive into the world of autonomous AI agents from scratch.

This course will guide you through the fundamentals of AI agents and introduce the innovative ReAct Prompting, which enables large language models (LLMs) to think and take actionable steps.

You'll learn how to build basic to real-world AI agents totally from scratch without using any third parties.

We will be building Agents by integrating custom functions that allow these models to respond intelligently to user queries and bypass limitations like accessing live data, APIs, and external functions.

Whether you're aiming to create a simple AI Agent or a real-world AI Agent, this course provides all the necessary codes and templates to get you started!


What's Inside The Course?

1- AI Agents Structure

You will understand what an AI Agent is and how it works.

2- Understand The ReAct Prompt

The ReAct Prompt is the heart of the AI Agent. We are going to see how it works within the AI Agent workflow in action.

3- Build a Basic AI Agent (Step-by-Step)

We will start by developing a fundamental AI agent that can use external functions to answer user queries.

4- Simplify AI Agents With SimplerLLM

We will build the same AI Agent with the Help of SimplerLLM Library and see how it simplifies our code.

5- Build an SEO Auditor AI Agent (Real Example)

After you understand How AI Agents work and how to build one, we will go with an Advanced Real-World Example and Build an SEO Auditor AI Agent.

6- Get all the Codes & Templates

Save time and effort with access to all my codes and templates


Requirements

This intermediate-level course requires attendees to have a foundational understanding of Python programming and core concepts of prompt engineering.

It is ideal for those who are comfortable with Python coding basics and want to expand their skills in practical AI applications.

Who this course is for:

  • Aspiring AI Developers: Individuals who want to expand their skills in practical AI applications.
  • Python Programmers with Intermediate Skills willing to dive into AI Projects and Applications.
  • Beginner prompt engineers eager to advance their skills.

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