Self-Paced Online Training · Only Python Required · Full Code Included

⌛ Lifetime Updates &  Lifetime Access 

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What You’ll Be Able to Build:

No fluff. No filler. Just Real AI agent skills that work.

 ✔ Build 10 diverse, end-to-end AI Agents Projects solving high-impact problems in healthcare, smart cities, finance and more using the latest multi-agent architectures.

✔ Start simple and go deep Building real-world AI agents across structured data, images, audio, and video in 5 progressive modules.

 ✔ Use LangGraph, Pydantic AI, CrewAI, OpenAI Swarm , and MCP (Model Context Protocol) to design multi-agent systems with Flow Engineering, modular context injection, and real task logic.

 ✔ Implement RAG with FAISS and ChromaDB, integrate ML models, and build agents that speak (ElevenLabs), see (LLaMA Vision), and act in real-time.

 ✔ Wrap it all into full-stack apps with Gradio, Folium, and Hugging Face, solve high-impact problems in healthcare, finance, aviation, and smart cities, including a Traffic Flow Analyzer and Vehicle Detection. 

What You’ll Build and Master:

01

Learn the Foundations of AI Agent Development

LLMs. Vision Models. Text to Speech. Custom Tools. Flow Engineering.

Get a clear grasp of what AI agents are, how they work, and the building blocks behind them: tasks, tools, workflows, and reasoning engines like GPT, Claude, LLaMA, DeepSeek and more.

02

Build Multi-Agent Systems with 4 Frameworks

Pydantic AI · LangGraph · CrewAI · OpenAI Swarm

Use PydanticAI, LangChain, LangGraph, CrewAI, and OpenAI Swarm to create AI systems that operate across medical teams, travel assistants, financial advisors, and airport agents, smart city traffic analysis and vehicle detection.

03

Build Domain-Specific & Custom AI Agents

Healthcare. Finance. Aviation. Smart Cities. Geoscience. Software.

You’ll build and customize agents across real industries using structured data, vision models, time series forecasting, and intelligent workflows.

Examples of AI Agents you’ll create:

• Physician Agent (with Patient Database Access)

• Radiologist Agent (Image Classifier for Medical Scans)

• Investment Advisor Agent (Personal Finance & Portfolio Insights)

• Hiring Agent (Screening for Technical Roles)

• Sales Agent (Selling Luxury & Specialized Products)

• Airport Agent (Face Detector for Check-In & Passport Control)

• Traffic Flow Analyzer Agent (Time Series Forecasting for Congestion)

• License Plate Detection Agent (Object Detection with Vision Models)

• Geo Agent (Location Intelligence via Folium Maps)

• Database Agent (Smart Retrieval from Structured Sources)

• Coding Agent (For Code Generation, Review & Debugging)

You’ll master how to adapt agents to different domains and make them truly usable, intelligent, and task-aware.

04

Build Retrieval-Augmented Generation (RAG)

FAISS Vector Database. ChromaDB Vector Database.

Learn how to build a complete RAG pipeline from embedding documents, to building vector databases, to running semantic search  enabling accurate, grounded, and context-aware responses from LLMs.

05

Work with Voice, Vision & Multi-Modal AI

Object Detection. Text to Speech. Image Classification. Face Recognition. OCR. Tabular Data.

Build agents that speak (via ElevenLabs), see (with vision models), and reason across text, image, video, and tabular data.

06

Use the Right Models and APIs for the Job

Hugging Face. Groq. Gradio. DeepSeek R1. GPTs. LLaMA. Together AI.

Work with GPT-4, Claude, LLaMA, and Groq via APIs for advanced reasoning and generation. Build interfaces with Gradio and visualize structured data with Folium.

Use Hugging Face to access 1.5M+ pre-trained models, and Together AI for high-performance vision APIs  powering use cases like pneumonia detection, license plate recognition, and vehicle detection.

07

Model Context Protocol (MCP) – Build Reusable, Configurable AI Agents

Reusable Agents · Server/Client Architecture · FastMCP · Stdio vs SSE

Master the full lifecycle of MCP-based agents — from context files and toolchains to deploying modular servers and clients that wrap around your AI agent logic.

You’ll build 3 complete MCP projects using Langchain and OpenAI SDK all inside VSCode:

• Air Quality Analyzer – Langchain Tools + vector-based retrieval

• News Summarizer – OpenAI SDK + Markdown output

• Math & Weather Agent – Langchain client-server pipeline

By the end, you’ll know how to architect portable, configurable AI agents that separate logic from context and run fast, flexibly, and reproducibly.

08

Advanced Topics — Enterprise-Grade AI Agents

9 Additional End to End AI Agents Project Ideas

After building 9 AI agent projects hands-on and step-by-step in the core modules, Advanced Topics expands your perspective with 9 additional project ideas across 9 different industries.

Rather than step-by-step builds, this module focuses on architecture, technology choices, system design, and curated code resources — enabling you to design, extend, and experiment with your own AI agent systems long after the course.

You’ll also learn how to use Gemini 3 Pro as a pre-agent for business and data understanding, accelerating analysis and system design before implementation.

+BONUS

AI Agent Zero to Hero – Deep Dive

Foundations. Agent Logic. Framework Comparison. Deployment Thinking. Strategy.

Get a structured overview of AI Agents — and a deep dive into how real-world systems are built, orchestrated, and deployed.

This 30-minute, 5-part module gives you the essential building blocks and strategic clarity to connect all the dots  from goals, tools, and memory... to reflection, collaboration, and long-term agent reasoning.

By the end, you won’t just understand AI agents  you’ll have built them.

Who This Is For

✔ For Whom

• Product builders & founders who need intelligent agents that actually work

• AI engineers and data scientists ready to move beyond prompts and into real-world agent design

• Developers who want to build full-stack, multi-agent AI systems, not toy projects

• STEM grads & researchers looking to enter industry with practical, deployable skills

• Technical professionals shifting into AI-driven roles

✔ Prior Knowledge

• Python: Basic to intermediate coding required. No need to be an expert.

• AI/ML Concepts: Familiarity recommended no need for a PhD.

✔ Hardware Requirements

• None: You’ll build everything using Google Colab fully hosted in the cloud. No local setup, no GPU needed.

If that sounds like you, you’re exactly who this training was built for.

Projects You’ll Build

Full Python code within Google Colab. VScode for MCP

1. Hospital AI System ≫ LangGraph Module

Build Physician, Radiologist, and Reception Agents, integrated into a Gradio dashboard with vision models and patient database retrieval.

2. Smart Airport Crew ≫ OpenAI Module

Automate Check-In, Passport Control, and Security Check using multi-agent coordination (Swarm) and face detection.

3. Financial Advisor Agent ≫ CrewAI Module

Design an intelligent agent that provides investment advice, personal finance breakdowns, and budget alerts with structured data.

4. Traffic Flow Analyzer ≫ PydanticAI Module

Forecast congestion using real-time data and time series agents with interactive plots and dashboards in Gradio.

5. License Plate Detection System ≫ PydanticAI Module

Detect and tag vehicle plates using object detection + Hugging Face models, and store results in a searchable vector DB.

6. Geo Intelligence Agent ≫ OpenAI Module

Use Folium to visualize maps, routes, and locations dynamically, ideal for Smart Cities or urban planning.

7. Travel Planner Agent ≫ CrewAI Module

Build a multi-agent system that selects destinations, books hotels, suggests itineraries, and responds via voice (ElevenLabs), all within a Gradio interface.

8. Air Quality Analyzer ≫ MCP Module

Build an MCP-based Langchain agent that analyzes pollution levels using external datasets as resource, with real-time insights via a modular client-server setup.

9.  News Summarizer Agent ≫ MCP Module

Use OpenAI SDK with MCP to create a news summarization agent that returns clean, markdown-style summaries, with stdio.

10.  Math & Weather Agent ≫ MCP Module

Design a minimal MCP client-server agent using Langchain that handles dynamic math questions and weather updates via multiple servers.

You’ll master world-class AI tools
Pydantic AI, LangGraph, CrewAI, OpenAI, and Swarm, and MCP by building real-world projects.

Why AI Professionals Trust This Training

✱ Trusted by engineers, PhDs, and real-world builders in 90+ countries.

Instructor

  Dr. Maryam Miradi - AI Expert, Educator, CEO & Chief AI Scientist

 Maryam's 20+ Years in AI

• 20+ Years of Hands-on Experience in AI Experience
• International AI Educator trusted by professionals in 90+ countries
• 200+ Data Scientists are coached by me 
• 160+ Projects in 12 Different Industries
• PhD in AI - Machine Learning & Deep Learning
• Best European AI Researcher in Future Vision
• 5 International Awards, 25 Publications & Books
• Author AI Agents: 50 Best Practices

Choose All Modules or Combine a Few.

✱ Get the full stack with the 5-in-1 bundle — and save 56%.