数据科学

Data Science

通过实际案例研究了解关键数据科学要点,包括R语言和机器学习,帮助你快速开始数据科学家的职业生涯。

哈佛大学

分享

  • 分类: 计算机
  • 平台: edX
  • 语言: 英语

课程概况

The demand for skilled data science practitioners in industry, academia, and government is rapidly growing. The HarvardX Data Science program prepares you with the necessary knowledge base and useful skills to tackle real-world data analysis challenges. The program covers concepts such as probability, inference, regression, and machine learning and helps you develop an essential skill set that includes R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with Unix/Linux, version control with git and GitHub, and reproducible document preparation with RStudio.

In each course, we use motivating case studies, ask specific questions, and learn by answering these through data analysis. Case studies include: Trends in World Health and Economics, US Crime Rates, The Financial Crisis of 2007-2008, Election Forecasting, Building a Baseball Team (inspired by Moneyball), and Movie Recommendation Systems.

Throughout the program, we will be using the R software environment. You will learn R, statistical concepts, and data analysis techniques simultaneously. We believe that you can better retain R knowledge when you learn how to solve a specific problem. Furthermore, HarvardX has partnered with DataCamp for all assignments, which use code checking technology that will permit you to get hands-on practice during the courses.

你会学到什么

1 基本的R编程技巧
2 概率,推理和建模等统计概念以及如何在实践中应用它们
3 获得tidyverse的体验,包括使用ggplot2进行数据可视化和使用dplyr进行数据争夺
4 熟悉掌握Unix / Linux,git和GitHub以及RStudio等数据科学家的基本工具
5 实现机器学习算法
6 通过激励现实世界的案例研究,深入了解基础数据科学概念

包含课程

数据科学:R基础知识
在R中构建基础并学习如何对数据进行争论,分析和可视化。本课程介绍常见的编程命令,如何操作矢量,以及何时使用高级功能(如排序)。

数据科学:可视化
学习基本数据可视化原理以及如何使用ggplot2应用它们。

数据科学:概率
在使用2007-2008金融危机案例研究学习关键概念时,获得概率论的重要基础知识,这对数据科学家至关重要。

数据科学:推理和建模
学习推理和建模:数据分析中使用最广泛的两种统计工具。

数据科学:生产力工具
数据科学项目涉及跟踪许多数据文件和分析脚本。学习GitHub,git,Unix / Linux和RStudio,以保持项目的有序性并生成可重现的报告。

数据科学:争吵
学习数据科学中不可或缺的一部分,称为数据争论,这一过程涉及将原始数据转换为进一步分析所需的格式。

数据科学:线性回归
了解如何使用R实现线性回归,这是数据科学中最常用的统计建模方法之一。

数据科学:机器学习
学习机器学习的基础知识,最流行和最成功的数据科学技术背后的科学,以建立电影推荐系统。

数据科学:Capstone
在这个顶点课程中,展示您从数据科学专业证书课程中学到的知识。您将有机会创建自己的长项目并进行评估。

工作前景

R在64%的数据科学职位发布中被列为必修技能,并且是2016年和2017年Glassdoor在美国的最佳工作。(来源:Glassdoor)
公司正在利用数据分析的力量来推动创新。 Google数据分析师使用R来跟踪广告定价趋势并阐明搜索数据中的模式。 辉瑞为R创建了定制包,因此科学家可以操纵他们自己的数据。
32%的全职数据科学家通过MOOC开始学习机器学习或数据科学,而27%的人是自学成才。 (来源:Kaggle,2017)
数据科学家数量少,需求量大。 (来源:TechRepublic)

细则

This program was supported in part by NIH grant R25GM114818.

HarvardX requires individuals who enroll in its courses on edX to abide by the terms of the edX honor code. HarvardX will take appropriate corrective action in response to violations of the edX honor code, which may include dismissal from the HarvardX course; revocation of any certificates received for the HarvardX course; or other remedies as circumstances warrant. No refunds will be issued in the case of corrective action for such violations. Enrollees who are taking HarvardX courses as part of another program will also be governed by the academic policies of those programs.

HarvardX pursues the science of learning. By registering as an online learner in an HX course, you will also participate in research about learning. Read our research statement to learn more.

Harvard University and HarvardX are committed to maintaining a safe and healthy educational and work environment in which no member of the community is excluded from participation in, denied the benefits of, or subjected to discrimination or harassment in our program. All members of the HarvardX community are expected to abide by Harvard policies on nondiscrimination, including sexual harassment, and the edX Terms of Service. If you have any questions or concerns, please contact harvardx@harvard.edu and/or report your experience through the edX contact form.

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