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 the course website
- Textbook: https://www.textbook.ds100.org/intro.html
- Assignments: refer to the course website
UCB Data100: Principles and Techniques of Data Science
Description
- Offered by: UC Berkeley
- Prerequisites: Data8, 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
- Records: refer to the course website
- Textbook: https://www.textbook.ds100.org/intro.html
- Assignments: refer to the course website
UCB Data100: Principles and Techniques of Data Science
课程简介
- 所属大学：UC Berkeley
- 先修要求：CS61A，线性代数
- 编程语言：Python
- 课程难度：🌟🌟🌟
- 预计学时：80 小时
伯克利的数据科学入门课程，内容相对基础，覆盖了数据清洗、特征提取、数据可视化以及机器学习和推理的基础内容，也会讲授 Pandas, Numpy, Matplotlib 等数据科学常用工具。其丰富有趣的编程作业也是这门课的一大亮点。
课程资源
- 课程网站：https://ds100.org/fa21/
- 课程视频：参见课程网站
- 课程教材：https://www.textbook.ds100.org/intro.html
- 课程作业：参见课程网站
UCB Data100: Principles and Techniques of Data Science
课程简介
- 所属大学：UC Berkeley
- 先修要求：Data8, CS61A，线性代数
- 编程语言：Python
- 课程难度：🌟🌟🌟
- 预计学时：80 小时
伯克利的数据科学入门课程，内容相对基础，覆盖了数据清洗、特征提取、数据可视化以及机器学习和推理的基础内容，也会讲授 Pandas, Numpy, Matplotlib 等数据科学常用工具。其丰富有趣的编程作业也是这门课的一大亮点。
课程资源
- 课程网站：https://ds100.org/
- 课程视频：参见课程网站
- 课程教材：https://www.textbook.ds100.org/intro.html
- 课程作业：参见课程网站
UCB Data100: Principles and Techniques of Data Science
课程简介
- 所属大学：UC Berkeley
- 先修要求：CS61A，线性代数
- 编程语言：Python
- 课程难度：🌟🌟🌟
- 预计学时：80 小时
伯克利的数据科学入门课程，内容相对基础，覆盖了数据清洗、特征提取、数据可视化以及机器学习和推理的基础内容，也会讲授 Pandas, Numpy, Matplotlib 等数据科学常用工具。其丰富有趣的编程作业也是这门课的一大亮点。
课程资源
- 课程网站：https://ds100.org/fa21/
- 课程视频：参见课程网站
- 课程教材：https://www.textbook.ds100.org/intro.html
- 课程作业：参见课程网站
UCB Data100: Principles and Techniques of Data Science
课程简介
- 所属大学：UC Berkeley
- 先修要求：Data8, CS61A，线性代数
- 编程语言：Python
- 课程难度：🌟🌟🌟
- 预计学时：80 小时
伯克利的数据科学入门课程，内容相对基础，覆盖了数据清洗、特征提取、数据可视化以及机器学习和推理的基础内容，也会讲授 Pandas, Numpy, Matplotlib 等数据科学常用工具。其丰富有趣的编程作业也是这门课的一大亮点。
课程资源
- 课程网站：https://ds100.org/
- 课程视频：参见课程网站
- 课程教材：https://www.textbook.ds100.org/intro.html
- 课程作业：参见课程网站