Foundations of Data Science: K-Means Clustering in Python

所在平台: CourseraArchive

课程类别: 其他类别

大学或机构: CourseraNew

课程主页: https://www.coursera.org/archive/data-science-k-means-clustering-python

课程评论:没有评论

第一个写评论        关注课程

课程大纲

Week 1: Foundations of Data Science: K-means Clustering in Python
Week 2: Means and Deviations in Mathematics and Python
Week 3: Moving from One to Two Dimensional Data
Week 4: Introducing Pandas and Using K-means to Analyse Data

课程评论(0条)

课程详情

Organisations all around the world are using data to predict behaviours and extract valuable real-world insights to inform decisions. Managing and analysing big data has become an essential part of modern finance, retail, marketing, social science, development and research, medicine and government. This MOOC, designed by an academic team from Goldsmiths, University of London, will quickly introduce you to the core concepts of Data Science to prepare you for intermediate and advanced Data Science courses. It focuses on the basic mathematics, statistics and programming skills that are necessary for typical data analysis tasks. You will consider these fundamental concepts on an example data clustering task, and you will use this example to learn basic programming skills that are necessary for mastering Data Science techniques. During the course, you will be asked to do a series of mathematical and programming exercises and a small data clustering project for a given dataset.

数据科学的基础:Python中的K-Means聚类:世界各地的组织都在使用数据来预测行为并提取宝贵的现实见识来为决策提供依据。管理和分析大数据已成为现代金融,零售,市场营销,社会科学,发展与研究,医学和政府的重要组成部分。 该MOOC由伦敦大学金史密斯学院的学术团队设计,将迅速向您介绍数据科学的核心概念,为您准备中级和高级数据科学课程做好准备。它侧重于典型数据分析任务所需的基本数学,统计和编程技能。 您将在示例数据集群任务中考虑这些基本概念,并将使用此示例来学习掌握数据科学技术所需的基本编程技能。在课程中,系统将要求您针对给定的数据集执行一系列数学和编程练习以及一个小型数据聚类项目。

课程标签

0人关注该课程

主题相关的课程