This course is the sixth of eight courses. This project provides an in-depth exploration of key Data Science concepts focusing on algorithm design. It enhances essential mathematics, statistics, and programming skills required for common data analysis tasks. You will engage in a variety of mathematical and programming exercises while completing a data clustering project using the K-means algorithm on a provided dataset.
Statistics and Clustering in Python
Statistics and Clustering in Python
本课程是 Data Science Foundations 专项课程 的一部分
位教师：Robert Zimmer
2,077 人已注册
包含在 
中
您将学到什么
In this course you will engage in a variety of mathematical and programming exercises while completing a data clustering project.
您将获得的技能
要了解的详细信息
了解顶级公司的员工如何掌握热门技能
积累特定领域的专业知识
本课程是 Data Science Foundations 专项课程 专项课程的一部分
在注册此课程时，您还会同时注册此专项课程。
- 向行业专家学习新概念
- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 获得可共享的职业证书
该课程共有4个模块
This week, we will delve into the core concepts of mean, variance, and other basic statistics, laying the groundwork for a solid understanding of data analysis principles. Through hands-on exercises and demonstrations in Python and Jupyter notebooks, we'll explore practical techniques for calculating and interpreting statistical measures.
涵盖的内容
10个视频7篇阅读材料10个作业1次同伴评审1个非评分实验室
This week, we will explore mathematics for multidimensional data. You will also learn how to work with multidimensional data in Python.
涵盖的内容
14个视频10篇阅读材料14个作业
This week, we will explore data manipulation and visualisation with Python's Pandas library. We will dive deep into the versatile capabilities of Pandas, empowering you to efficiently manipulate, analyse, and interpret data.
涵盖的内容
6个视频6篇阅读材料7个作业1次同伴评审
This week, we will embark on a journey through the fascinating world of unsupervised learning, where patterns emerge from data without explicit guidance. You will implement the K-means algorithm to solve a real-world problem.
涵盖的内容
8个视频3篇阅读材料3个作业3次同伴评审5个讨论话题
获得职业证书
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位教师
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