30 Days of Python: Coding for Beginners -(2026)

Mastering Model Context Protocol (MCP) is a practical, engineering-focused course designed to help developers build real, secure, and production-ready AI backends. After helping thousands of students overcome confusion around LLM integration, tool calling, and backend architecture, I created this course to solve the most common problems: “How do I build a reliable backend that LLMs can call safely?” “How do I choose between SSE, stdio, or streamable-http?” “How do I scale MCP into real applications with FastAPI, Auth0, and LangGraph?” “How do I structure my MCP tools, resources, prompts, and context?” In this course, I guide you step-by-step—from spinning up a minimal MCP server to deploying a fully secure, Dockerized system. Every lesson is hands-on, designed to remove complexity and give you a clear, repeatable workflow for building modern AI systems. If you're frustrated by vague tutorials and want a clear, concrete, engineering-level understanding of MCP, this course is built for you.

This course is built from real-world experience designing and deploying production-grade LLM applications on Azure. Rather than focusing on toy examples or isolated notebooks, I guide students through the exact challenges they face when moving from experimentation to real systems: data ingestion, vector storage, service orchestration, cloud deployment, and security. Throughout the course, I break down complex Azure services into clear, practical steps, explain why each architectural decision is made, and show how components work together in a scalable system. Students learn by building, debugging, and deploying a complete LangChain-based application, gaining confidence in solving real infrastructure and application-level problems.

In this course, you will learn how to design, build, and evaluate advanced RAG systems using the LangChain framework. You will master LCEL, Runnables, advanced retrieval techniques, chunking strategies, cross-encoder reranking, agent-based RAG, tool calling, SQL integration, and safety techniques using NeMo Guardrails. You will also learn how to trace, debug, and deploy a full-stack AI chatbot with LangFuse, React, FastAPI, and Docker.

What to Expect from This Course Welcome to LangGraph in Action, your ultimate guide to mastering the design and deployment of advanced AI agents using LangGraph. In this course, you’ll explore the fundamentals of building modular, scalable, and production-ready agents, all with a hands-on approach. From understanding the basics of LangGraph’s state-based design to creating a full-stack application, you’ll gain the skills needed to bring AI agents to life. Course Highlights State-Based Design: Dive into LangGraph’s core philosophy of nodes and edges to create structured, maintainable agents. Memory Management: Explore short-term memory with checkpointers and long-term memory with the Store object to enable agents that adapt and learn. Advanced Workflows: Build human-in-the-loop systems, implement parallel execution, and master multi-agent patterns. Production-Ready Development: Learn asynchronous operations, subgraphs, and create full-stack applications using FastAPI and Docker. By the end of the course, you’ll not only have a strong theoretical understanding but also the practical skills to deploy AI agents anywhere, entirely with open-source tools. Whether you're a developer aiming to stay ahead of the curve or a seasoned engineer looking to expand your AI toolkit, this course equips you for the rapidly growing field of AI agents. With the increasing adoption of AI agents in real-world applications, this course ensures you're prepared to design, build, and deploy advanced systems that solve practical challenges. Let’s start building and shaping the future of AI together!

Are you having trouble integrating payments for your web service? Quickly apply payments to your service with Django and Import.

This course delves deeper into the program or file structures that we take for granted or commonly encounter, using Python.

Learn how to start developing a web app project using Django (2.0 or later), and use the content to create a simple non-member bulletin board site that can be run on AWS.

Strengthen your coding skills through coding test problems by learning Python-based data structures and algorithms!

This course provides a complete introduction to programming with Python. You will start from the very basics and gradually build up to writing more advanced scripts and solving real-world coding challenges. With step-by-step explanations, practical exercises, and projects, this course is perfect for anyone looking to start their coding journey or strengthen their foundation in Python.

Stop worrying about the dev team - I'll build it myself now! This course helps professionals in planning, marketing, sales, and other practical roles implement core web service features on their own using AI tools, without needing developer assistance.

If you are planning a service, a website is an essential element. Of course, in addition to the service, most of the currently provided program infrastructures operate based on the web. The purpose of this course is to learn how to create a website using Python, which is considered the easiest programming language, and how to set it up to an actual operational state.

Create Your Own Data Analysis Portfolio with GEMINI CLI Vibe Coding - Start Without Any Charges Data Collection, Analysis, Reports, Dashboard Creation, and Work Automation Even if you're new to data collection, once you learn the principles, prompt writing methods, and how to use VSCode, you can perform data collection, analysis, visualization, reports, and dashboard creation just like a data analyst. From Python Data Collection to Analysis Report Writing with GEMINI CLI and VSCode Prompt Writing and Error Resolution Methods for Foolproof Data Collection and Analysis

I wanted to briefly cover the basics of Python through Jupyter Notebook, which allows you to immediately check the results of your coding.

Solve coding test problems using Python.

Using the ChatGPT API, develop a full-stack multilingual translator web application in just 30 minutes, and even if you know nothing about AI, try incorporating the latest AI (ChatGPT API) into your product!

You will learn techniques that can be applied in various fields of IT security, starting from the introduction to Python programming.

Let's create a Jeju Olleum map guide service using public data and Folium! It's not a service that only I can see, but a service that others can access! It's not a portfolio that I have as a file, but a service that others can access!

Learn to implement Telegram, Slack, KakaoTalk, and Discord bots with Python, exploring each service's features via various examples.

This course covers the process of automating algorithmic trading in local and cloud environments, and focuses on hands-on practice.

The goal is to master the complex GPT API and Python in the easiest way possible through hands-on practice. You will develop a YouTube video summarization AI using the latest ChatGPT API and implement it as a web application using Streamlit.

A course where you can not only build programs required for blog operation using Python, but also earn additional revenue through sales and branding.

Online bootcamp in Jeju! Create your own service quickly! :)

Even office workers who know nothing about coding can easily learn the basic concepts and grammar of programming through practice, and learn file input/output, Excel data processing, automatic creation of MS-Word documents, graph drawing, web scraping, etc.

We will build a web app environment with dJango and create a web crawling app using scrapy, a web crawling framework.