*开始时间: 04/16/2018
持续时间: Unknown*

所在平台: Coursera专项课程 课程类别: 计算机科学 大学或机构: CourseraNew |

课程主页: https://www.coursera.org/specializations/jhu-data-science

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Ask the right questions, manipulate data sets, and create visualizations to communicate results. This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material.

10 courses

The Data Scientist’s Toolbox

Current session: Apr 16

In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components

R Programming

Current session: Apr 16

In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language

Getting and Cleaning Data

Current session: Apr 16

Before you can work with data you have to get some. This course will cover the basic ways that data can be obtained. The course will cover obtaining data from the web, from APIs, from databases and from colleagues in various formats. It will also c

Exploratory Data Analysis

Current session: Apr 16

This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques

Reproducible Research

Current session: Apr 16

This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code

Statistical Inference

Current session: Apr 16

Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of des

Regression Models

Current session: Apr 16

Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions. Regression models, a subset of linear models, are the most important statistical analysis tool in a data scientist’s toolkit. Thi

Practical Machine Learning

Current session: Apr 16

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical appli

Developing Data Products

Current session: Apr 16

A data product is the production output from a statistical analysis. Data products automate complex analysis tasks or use technology to expand the utility of a data informed model, algorithm or inference. This course covers the basics of creat

Data Science Capstone

Upcoming session: Apr 30

The capstone project class will allow students to create a usable/public data product that can be used to show your skills to potential employers. Projects will be drawn from real-world problems and will be conducted with industry, government, an

约翰霍普金斯大学的数据科学专项课程系列（Data Science Specialization），这个系列课程有10门子课程，包括数据科学家的工具箱，R语言编程，数据清洗和获取，数据分析初探，可重复研究，统计推断，回归模型，机器学习实践，数据产品开发，数据科学毕业项目，感兴趣的同学可以关注: Launch Your Career in Data Science-A nine-course introduction to data science, developed and taught by leading professors.