🚀 Python to Agentic AI Engineering Course (GCP Stack)

From Beginner to Production-Ready AI Agents using Google's AI Stack

Welcome to the official repository for the Python to Agentic AI Engineering course.

This repository will contain the source code, practice exercises, assignments, notes, and projects used throughout the course.

Whether you're a beginner starting your programming journey or a developer looking to build AI Agents, this course is designed to help you learn through practical examples and real-world projects.

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🎯 Course Objectives

By the end of this course, you will be able to:

• Build Python applications from scratch
• Work with APIs using Python
• Understand Large Language Models (LLMs)
• Build AI applications using Gemini API
• Use Google AI Studio
• Create tools for LLMs
• Build AI Agents using Google ADK
• Develop Multi-Agent Systems
• Deploy AI applications

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📚 Course Outline (It is still work in progress)

Module 1 - Python Foundations

• Introduction to AI and Python
• Variables and Data Types
• Lists, Dictionaries & Conditional Statements
• Loops, Functions & Parameters
• Object-Oriented Programming
• Files, JSON & Modules

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Module 2 - Python for AI Engineers

• APIs and Requests
• Async Python

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Module 3 - LLM Foundations

• Understanding LLMs

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Module 4 - Building AI Applications

• Google AI Studio
• Gemini API with Python
• Tool Calling
• Structured Output

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Module 5 - Agent Fundamentals

• What is an AI Agent?
• Agent Architectures

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Module 6 - Google ADK

• Introduction to Google ADK
• Agents & Tools
• Memory & State

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Module 7 - Multi-Agent Systems

• Multi-Agent Basics
• Advanced Multi-Agent Systems

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Module 8 - Production AI

• Deploying AI Agents
• Capstone Project

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💻 Prerequisites

You don't need any prior programming experience.

Recommended:

• Python 3.12+
• Visual Studio Code
• Git
• GitHub Account
• Google Account

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📖 Learning Approach

Every session follows the same pattern:

1. Learn the concept
2. Live coding
3. Practice exercises
4. Small challenge
5. Build something useful

The goal is not just to understand concepts but to apply them.

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🏋️ Practice

Learning happens by writing code.

After every session:

• Complete the exercises
• Modify the examples
• Experiment with your own ideas
• Try solving the challenge before looking for help

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❓ Asking Questions

Before asking a question, please include:

• What you were trying to do
• Expected result
• Actual result
• Error message (if any)
• Relevant code snippet

Example:

Problem:
Dictionary iteration is not working.

Expected:
Print all keys.

Actual:
TypeError

Code:
...

This helps everyone understand and solve problems faster.

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🤝 Community Guidelines

Please remember:

• Be respectful.
• No question is too basic.
• Help fellow learners when possible.
• Search existing discussions before posting.
• Keep discussions related to the course.

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🚀 Projects

Throughout the course, we will build practical applications, including:

• Weather Application
• API Integrations
• Resume Analyzer
• Gemini Chat Applications
• AI Research Assistant
• AI Tools
• AI Agents
• Multi-Agent Systems

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📌 Course Resources

This repository will be updated regularly with:

• Session code
• Practice questions
• Assignments
• Sample projects
• Additional learning resources

Please Star ⭐ this repository to stay updated with new content.

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⚠️ Disclaimer

This repository is intended for educational purposes.

The code and examples are provided to help learners understand concepts and build their own projects. You are encouraged to experiment, improve, and extend the examples as part of your learning journey.

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⭐ Support the Project

If you find this course helpful:

• ⭐ Star this repository
• 🍴 Fork it to maintain your own learning progress
• 📢 Share it with others who want to learn Python and AI