Concepts: project management, Notion AI, and time management-(2026)

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.

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.

Course Summary: In this Masterclass, you’ll master AI-driven development using Claude Code, an agentic coding tool that fits naturally into real-world workflows. You’ll automate repetitive tasks with slash commands, create custom hooks, and adopt a spec-driven workflow to stay in control as projects grow. Learn how to extend Claude Code with MCP servers, plugins, and subagents, integrate it directly with GitHub and the web, and deploy applications on Vercel. This course solves developers’ productivity challenges and helps them leverage AI to build applications faster and more efficiently.

This course is designed to help absolute beginners learn Python through short, focused, and practical lessons. With daily bite-sized sessions of about 15 minutes, I guide students step by step through the core concepts of Python, making coding approachable and less overwhelming. Based on my experience helping beginners overcome common learning obstacles—such as confusion around syntax, logic, and problem-solving—I emphasize clarity, repetition, and hands-on practice. Each lesson builds on the previous one, reinforced by practical exercises and regular rest days for review and consolidation. By the end of the 30 days, students will not only understand Python fundamentals but will also confidently build their own command-line Python application, connecting all the concepts learned throughout the course.

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.

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!

"This is a course for learning the overall usage of Notion, an all-in-one productivity tool that enables efficient management of work and life in a Mac environment. You can learn step-by-step from Notion's basic functions to databases, automation, AI utilization, and practical template creation, acquiring work and self-management methods optimized for Mac users. Through a hands-on curriculum, you can increase productivity in both daily life and work."

Say goodbye to complicated collaboration tools! 👋 From Markdown to databases, the essential skills of a workaholic can be done with Notion 🚀

"This is a course for learning the comprehensive usage of Notion, an all-in-one productivity tool that enables efficient management of work and life in a Mac environment. You can learn step-by-step from Notion's basic functions to databases, automation, AI utilization, and creating practical templates, acquiring work and self-management methods optimized for Mac users. Through a hands-on curriculum, you can increase productivity in both daily life and work."

Jira is the most suitable 'collaboration' and 'communication' tool for applying Agile techniques within organizations, which have recently become an issue!

Acquire an administrator role for agile document management in our organization!

This course is for those who want to use JIRA to perform team work more efficiently. It explains the basic background knowledge for using JIRA, project creation, management, issue registration/management, and helps you understand the agile project execution lifecycle such as Scrum and Kanban and apply it to actual work.

This is a basic course for those who are new to product CE certification.

2024 Smartsheet Korean Latest Lecture. Let's learn how to use forms, reports, dashboards, etc. with practice.

3 projects that compress 20 carefully selected concepts will build 80% of your n8n skills.

How to Build an Efficient Startup Workflow System with Just Notion 🧑🏻‍💻 (Practical Workflow Templates Provided by Practitioners)