This part of the project focuses on setting up the Python development environment in a style suited for developers rather than academic settings. It introduces Google Colab as an alternative development environment, especially for those with slower computers. The modules cover basic Python operations, including variables, strings, lists, dictionaries, and control structures (if statements and loops). It also delves into file handling and provides a gentle introduction to web development concepts that are beneficial for web crawling.

• Python Development Environment Setup (Developer Style)
• Using Google Colab for Development
• Basic Python: Variables, Strings, and Computer Control
• Data Handling with Python: Lists and Dictionaries
• Control Structures: If Statements
• File Handling in Python
• Loops in Python: Mastery through Practice
• Web Crawling with Python: Accessing Web Pages and Extracting Required Information
• Case Studies for Independent Code Writing
• Function Syntax in Python: Practical Usage
• Web Crawling Projects: Applying Functions in Real Scenarios
• Handling Infinite Scroll Data Collection (Example: Naver Blog)

In this section, the focus shifts towards automation and dealing with various data formats such as JSON. It includes practical projects like creating Instagram bots, dealing with cryptocurrency data, and publishing automated blog posts on platforms like Naver. It also covers advanced Python topics like multi-threading, os module, and object-oriented programming.

• Handling JSON Data: Cryptocurrency Prices and Timestamps
• Python Multi-threading for Large Scale Data Collection
• Creating Instagram Bots: Installation, Data Collection, Auto Login, Page Navigation, and Image Collection
• Automated Blog Publishing on Naver: Login Bypass and Content Posting
• File Handling with OS Module
• Understanding and Applying Class/Object Syntax in Python
• Web Crawling Defense and Penetration: Case Study on Amazon.com

The final part covers data analysis and visualization using Python. It includes handling large datasets, resizing and compressing images, sending email notifications, and statistical analysis with Pandas. It also covers time-series data analysis, data visualization with Matplotlib, and creating automated translation services using APIs. Advanced topics like regression analysis and polynomial regression are also included.

• Handling Large Image Datasets: Resizing and Compression
• Sending Email Notifications with Python (SMTP)
• Data Analysis with Pandas: A Faster Alternative to Excel and SQL
• Regular Expressions: Core Concepts and Applications
• Time-Series Data Analysis with Moving Averages
• Data Visualization: Quick Mastery of Matplotlib
• Automated Translation Service using APIs (Papago)
• Regression Analysis: Understanding and Predicting Data Relationships

This comprehensive tutorial series is aimed at individuals who wish to gain an in-depth understanding of Python, web crawling, automation, data analysis, and visualization. Each section is meticulously designed to ensure a thorough understanding of the concepts and practical application through real-world examples and projects.