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docs/数据科学/Data100.en.md Normal file
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# UCB Data100: Principles and Techniques of Data Science
## Description
- Offered by: UC Berkeley
- Prerequisites: CS61A，Linear Algebra
- Programming Languages: Python
- Difficulty: 🌟🌟🌟
- Class Hour: 80 hours
This is Berkeley's introductory course in data science, covering the basics of data cleaning, feature extraction, data visualization, machine learning and inference, as well as common data science tools such as Pandas, Numpy, and Matplotlib. The course is also rich in interesting programming assignments, which is one of the highlights of the course.
## Resources
- Course Website: <https://ds100.org/fa21/>
- Records: refer to course website
- Textbook: <https://www.textbook.ds100.org/intro.html>
- Assignments: refer to course website

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docs/编程入门/MIT-Missing-Semester.en.md
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- Offered by: MIT
- Prerequisites: None
- Programming lanuages: Shell
- Programming Languages: Shell
- Difficulty: 🌟🌟
- Class Hour: 10 hours
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- Homepage: <https://missing.csail.mit.edu/>
- Records: <https://www.youtube.com/playlist?list=PLyzOVJj3bHQuloKGG59rS43e29ro7I57J>
- Assignments: Some exercises behind each lecture.
- Assignments: Some exercises after each lecture.