Web Data Transfer with Python

Course Description

Welcome to "Web Data Transfer with Python," an essential course for anyone looking to harness the power of Python in the digital age. This introductory-level course, offered by AnahuacX, is designed to equip you with the fundamental skills needed to navigate, analyze, and retrieve data from the web and application programming interfaces (APIs).

In today's data-driven world, understanding how to interact with web-based information is crucial. This course will take you on a journey through the intricacies of web data transfer, teaching you to recognize architectures, utilize common expressions, and leverage specialized libraries for data interpretation.

What You'll Learn

• Recognition of web data transfer protocols for information retrieval
• Accessing, retrieving, and analyzing data from websites and APIs
• Data recovery in HTML, XML, and JSON formats using regular expressions and specialized Python modules
• Creation of REST-based Application Programming Interfaces (APIs)

Prerequisites

This course is designed for beginners, and there are no specific prerequisites. However, a basic understanding of Python programming would be beneficial.

Course Coverage

• Internet fundamentals and web data access
• Hypertext Transfer Protocol (HTTP)
• Regular Expressions
• Web Scraping techniques
• HTML syntax and structure
• Interpreting web data using Regular Expressions and BeautifulSoup
• Web Services and XML
• Parsing XML
• Application Programming Interfaces (APIs): Functions, Methods, and Security
• JavaScript Object Notation (JSON) and parsing
• REST Architecture
• Creating APIs with Flask and Flask-RESTful
• Making HTTP requests to Flask API using Postman

Who This Course Is For

• Aspiring data scientists and analysts
• Web developers looking to expand their skill set
• Students interested in learning about web data manipulation
• Professionals seeking to enhance their Python programming abilities
• Anyone curious about how data moves across the internet

Real-World Applications

1. Data-driven decision making in business
2. Automating data collection for research projects
3. Building web applications that interact with various data sources
4. Developing custom APIs for internal or external use
5. Enhancing website functionality through data integration
6. Conducting market research and competitor analysis
7. Creating data visualization tools for web-based information

Syllabus

Conclusion

By the end of this course, you'll have a solid foundation in web data transfer using Python, giving you a competitive edge in the rapidly evolving world of data science and web development. Don't miss this opportunity to expand your skill set and open new doors in your career. Enroll now and start your journey into the fascinating world of web data manipulation with Python!