Master calculus 2 using Python: integration, intuition, code

Develop a deep understanding and intuition for calculus. Solve problems and implement algorithms by hand and in Python.

From Python fundamentals to practical data analysis! You will learn practical Python skills for processing, visualizing, and analyzing data while solving business problems.

How did Assistant Manager Kim, who worked overtime every day, become a "leave-on-time pro" in just 1 hour? The secret to reclaiming your "clock-out time" Staying up all night because an Excel formula broke, or having an entire report ruined by a single typo—every office worker has experienced this at least once, right? This course was designed to put an end to that "recurring pain." You don't need to memorize complex coding syntax. We utilize Cursor AI, an AI-powered tool that writes code based on text commands, and Streamlit, which allows anyone to easily create websites. I have captured the entire process of solving the "pain points" I personally faced in the field—such as merging files by branch, automatically classifying items for repair, and generating infinite PDF certificates—all by "conversing" with AI without typing a single line of Python code yourself. By the end of this course, you will be reborn not as a mere office worker, but as a "Digital Transformation Expert" who revolutionizes your team's work efficiency.

A Complete End-to-End Developer Journey — Build Lightning-Fast APIs, Modern Frontend Interfaces, Real Projects, Authentication Systems, Dashboards & Full Deployments Using FastAPI, React, and Vibe Coding Techniques.

Build an AI agent from scratch using Python and a single while loop, without any frameworks. In the introductory section, you’ll add tool design, failures and costs, memory, human approval, evaluation, and a web interface one by one to complete a small coding agent. In the hands-on section, you’ll implement RAG, multi-agent systems, and an MCP server yourself using real business reports from DART, then compare them numerically with LangChain and LangGraph.

Even if you're new to Python, this course will help you read and write expert-level code!

This course proceeds with Python theory and practical sessions that even non-majors can easily understand. This is the first step in the overall roadmap built for application development - the Python programming introduction course. [Complete-Roadmap] Python Basics->Advanced Python->Automated Trading-Backtest Development->Automated Trading-Real-time Development->Automated Trading-LLM Application

Through this course, you will learn the basics of optimization theory for multivariable functions and gain a comprehensive understanding of vector functions.

This is a process for completing IoT products without complex coding, using the Vibe Coding methodology powered by AI agents. You can experience the entire product development cycle in a condensed format—from embedded hardware control and AI vision recognition to PCB design, 3D printing, and web/app service development—allowing you to launch functional, commercial-grade IoT devices.

Are you just telling Claude Code, “Build it for me”? It works well at first. But as the project grows, the AI modifies the wrong files, forgets the rules, and repeats the same mistakes. In this course, you’ll learn how to leverage **the latest Claude Code** to delegate coding while still keeping the developer in control of **design, permissions, context, and verification**. **Design → Plan → Implement → Test → GitHub PR** Based on the developer’s judgment and review, AI-powered development automation is applied throughout this entire process.

This course consists of 41 lessons and approximately 22 hours of training on designing and implementing backend APIs with FastAPI. FastAPI is a framework that is easy to get started with. Skim the documentation, write a few lines, and your API is up and running. The problem comes afterward. If you don’t know how a request travels to reach a function parameter, when dependencies are cleaned up, or where exceptions are caught, you can quickly get stuck as soon as things become even slightly more complex. This course spends time tracing how things work internally. We begin with the development environment. You’ll learn both conda and venv, send requests using the VS Code REST Client and Swagger UI, and become familiar with the structure of HTTP requests and responses. Next, we cover the difference between path parameters and query parameters, explaining why 422 errors occur in connection with type checking. Pydantic is the area explored most deeply in this course. After covering everything from scalar types to dates, UUIDs, Decimal, Enum, and Literal, we move on to BaseModel. We use Field() to define constraints, validate single and multiple fields with @field_validator, and examine the differences between the before and after behaviors of @model_validator. Since the course is based on Pydantic v2, you can apply the latest syntax directly in real-world projects. The middle section focuses on structure and dependency injection. We cover how to split files using APIRouter, how to use functions and classes as dependencies, Sub-dependencies, and decorator-level dependencies in sequence. Four lessons are dedicated to yield. We delve into how generators work, how exceptions are passed back up the call stack with raise, and how exceptions can be injected at the yield point using throw(). Understanding how resource cleanup works in dependencies that include yield makes DB session management much clearer. The latter part covers authentication and databases. We organize the concepts of OAuth 2.0 and its four Grant Types, then implement JWT issuance and verification, the internal execution logic of OAuth2PasswordBearer, and authorization control using Security() and scopes. We then configure Google, Kakao, and Naver clients ourselves and add social login using the Authorization Code Grant flow. Finally, we cover the SQLAlchemy ORM, including the URL structure of create_engine, the roles of the Dialect and DBAPI, transactions, sessions, and model and table creation. This course is suitable for anyone who wants to understand not only "working code" but also "why it works that way.&quot

Everyone says agents are the trend, but why does your work stay the same? Have you been blocked by the "alien language" of APIs, stuck at tool installation, or found that what you learned doesn't translate to actual work? This integrated course connects the entire process into "one single path"—from the principles of API and communication structures to creating your own agent through Vibe Coding, and automating practical tasks like reports, Excel, and content with Claude Code. Whether you start from the basics or aim for professional application, you will complete the journey without interruption. (Windows recommended)

"Are you still studying with coding books?" A course, rated 5.0/5.0 by MBA and business undergrads at a London management university. You can take AI data analysis lectures from home. Even for humanities-background non-majors: practical data analysis skills immediately usable in the field, plus a data analysis portfolio for job search completion. I am a British Professor (British Professor) teaching data analysis and project classes with ChatGPT, no coding knowledge required.

"Will you make money just by building an app? No." Vibe Coding is merely a tool; the core is 'profitable planning and strategy.' This course goes beyond simple Vibe Coding technical training to reveal a practical manual for building a revenue automation system, learned firsthand by a non-developer operating 200 apps.

- Practical Kaggle Competition Project: From Data Exploration to Submission - Beyond Tutorials: Follow a Real Kaggle Competition from Start to Finish Have you signed up for Kaggle and completed the Titanic tutorial, only to feel lost about where to start when facing a real competition? If you simply copy someone else’s notebook and submit it, you’ll eventually hit the wall of wondering, "Why isn’t my score improving?" In this course, we’ll work through an actual Kaggle competition from start to finish, covering data exploration, validation design, feature engineering, modeling, and submission. Instead of memorizing code, you’ll develop an intuitive understanding of the competition mindset: “What should I try and why, and how can I validate its effectiveness?” [One line about your competition participation, awards, or practical experience]

For those who want to learn data science, big data, and web scraping, (1) we summarize the most essential Python syntax in a short time, and (2) help you become familiar with Python and web scraping through practical scraping programming.

If you feel lost about what to learn in an era where AI writes code, you can find clear answers in the principles of UNIX and the kernel—the unchanging essence of systems. Through a practical project that integrates Node.js with a C language engine (FFmpeg), this course delivers the perspective of the top 1% of architects who command entire systems without being swayed by technology trends.

This class will teach you what effects you can get when you introduce Python into a website created in WEB1.

We will develop a web app that collects data using concurrent/parallel programming in Python, loads it into MongoDB, analyzes it, and visualizes the collected data using FastAPI, a modern web framework. In the process, you will learn and understand Python concurrent/parallel programming using coroutines, multi-threading, and multi-processing, and understand how to use them to improve Python's performance. We will help you apply Python concurrent/parallel codes directly to your work. We will not only teach you how to develop and end, but also how to deploy and operate an actual app on the AWS cloud.

This is a course on building your own stock and cryptocurrency automated trading programs using ChatGPT, even without prior coding knowledge. You will gain both AI development skills and financial investment knowledge through hands-on practice covering the entire process, from data collection to predictive model development, stock recommendation systems, and actual automated trading.