This is a comprehensive practical course for everyone, from developers new to Claude Code to those who want to actively utilize AI in their professional work. In this course, you will learn step-by-step, starting from the basic concepts and natural language processing principles of Claude Code to installation, conversation and session management, model and effort settings, and context management. Afterward, you will master practical development methods that can be immediately applied to real projects, such as codebase exploration, writing accurate prompts, bug debugging, TDD workflows, refactoring, and automated quality control using Hooks. Furthermore, it systematically covers the latest AI development processes using Claude Code, including Git PR code reviews, GitHub Actions automation, parallel development using Git Worktree, Skills development, sub-agent configuration, multi-agent collaboration, team standardization and onboarding, and technical documentation. The course is structured around examples and projects that can be directly applied in the field, allowing you to build development capabilities for real-world tasks rather than just learning simple features. You will fully master a new way of developing—collaborating with AI to maximize development productivity using Claude Code.

This course focuses on practical training in the core foundations of data analysis and data preprocessing using NumPy and Pandas. You will learn step-by-step, starting from Python's basic data structures to NumPy arrays and Pandas DataFrames, and master various processing techniques for analyzing real-world data. By practicing the most frequently used functions in data analysis—such as data cleaning, transformation, merging, and grouping—you can naturally improve your data preprocessing skills for machine learning. The course provides both conceptual explanations and hands-on exercises so that even beginners can easily follow along, allowing you to build a solid foundation for data analysis and machine learning.

Data visualization is an essential skill for effectively communicating data and supporting decision-making. This course is designed for beginners learning Tableau for the first time, offering a practice-oriented curriculum that covers everything from basic data visualization concepts to creating various charts and data analysis techniques. Through this course, you will gain hands-on experience with frequently used practical features, including Tableau installation, data connection, creating various charts, calculated fields, trend lines, box plots, histograms, and highlight tables. In addition, you will learn core concepts necessary for data analysis, such as data literacy, data visualization strategies, correlation analysis, and outlier analysis. Even complex functions are explained step-by-step at a beginner's level, allowing those new to Tableau to follow along without any pressure.