Build AI Agents with Python
- Description
- Reviews
In this project-based course, you will learn how to design, build, and deploy intelligent AI agents using Python. Through hands-on coding sessions, you’ll explore how to create multi-agent systems that can think, reason, and take action autonomously.
You will build real-world projects using Ollama for local model execution, the OpenAI SDK for GPT-powered intelligence, CrewAI for multi-agent orchestration, Spitch for voice and speech integration, and LangChain for building advanced reasoning and tool-using agents. Every module takes you from concept to working code, combining AI logic with real business applications.
By the end of this course, you won’t just understand how AI agents work, you’ll have built your own production-ready systems, integrated APIs, deployed agents that solve real problems, and earned a certificate of completion to showcase on your LinkedIn profile or portfolio.
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A laptop with a stable internet connection
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Basic familiarity with Python
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Curiosity about AI systems and problem-solving with code
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Commitment to experiment and learn by building
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Developers who want to master AI agent engineering in Python
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Tech enthusiasts and students eager to build intelligent automation tools
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Entrepreneurs and freelancers aiming to launch AI-powered solutions
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Researchers and product builders exploring the next frontier of applied AI
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Overview of what you'll build -
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Architecting the solution - CLI Agent
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10
Installing Ollama
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11
Downloading models with Ollama
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12
Setting up the project - CLI Agent
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13
Loading the document - CLI Agent
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14
Building the CLI Questionnaire Agent
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15
Defining the prompt - CLI Agent
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16
Generating questions via Llama 3.1
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17
Creating the evaluation function
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18
Building the CLI Agent runner
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Testing the CLI Agent
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20
Overview of what'll build - Mini-Course Agent
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21
Architecting the Mini-Course Agent
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22
Creating an OpenAI API Key (Langchain)
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23
Process file and URL for LangChain Agent
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24
Defining tools in LangChain Agent
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25
Initialize the LangChain Agent
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26
Testing the LangChain Agent on terminal
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27
Creating the Streamlit App
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28
Testing the Mini-course generator
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29
Overview of what you'll build
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30
Architecting the Podcast Agent
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31
Installing libraries - Podcast Agent
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32
Setting up Tavily Search Tool
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33
Defining the agents with CrewAI
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34
Defining the tasks with CrewAI
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35
Agent orchestration - CrewAI
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36
Building audio generation using OpenAI TTS
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37
Creating the frontend with Streamlit
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38
Testing the Podcast Agent
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39
Getting Started with Spitch
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40
Creating API Keys on Spitch
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41
Overview of the Spitch project
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42
Architecting the Spitch project
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43
Project and LLM setup (Spitch)
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44
Setting up TavilySearchTool (Spitch)
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45
Defining the agents (Spitch)
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46
Orchestrating tasks across agents (Spitch)
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47
Audio and Zipfile generation using Spitch TTS
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48
Creating the Streamlit UI (Spitch)
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49
Testing the Podcast Agent (Spitch)
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