Online courses directory (1116)

The French Revolution was one of the most important upheavals in world history. This course examines its origins, course and outcomes.

本课程讨论人、媒介、信息在社会化媒体环境下的新规律。The course introduces students to regular patterns of interaction among people, media and information under our surrounding social media .

课程从喜闻乐见的唐诗宋词入手，触摸一段历史与一群文人的体温，领悟人生旅途的趣味和智慧。

In this course----the third in a trans-institution sequence of MOOCs on Mobile Cloud Computing with Android--we will learn how to connect Android mobile devices to cloud computing and data storage resources, essentially turning a device into an extension of powerful cloud-based services on popular cloud computing platforms, such as Google App Engine and Amazon EC2.

媒介批评是立足于批判的价值立场，对媒介活动及其产品和传播观念进行研究。

刑法是规定犯罪与刑罚的法律。刑法学是研究刑法的科学，主要研究犯罪的成立条件以及刑罚的种类与适用刑法的制度等问题。本课程的主要目的是简明完整地说明现代刑法学总论的基本概念、基本理论与基本方法。

This course deals with international relations, peace and security and brings together a number of experts from the field and academia to share their perspectives. The course will help you gain insight into conflict resolution and the role organizations such as the United Nations Security Council, the European Union, the African Union and NATO play in a changing world.

Get an overview of the data, questions, and tools that data analysts and data scientists work with. This is the first course in the Johns Hopkins Data Science Specialization.

Learn how to program in R and how to use R for effective data analysis. This is the second course in the Johns Hopkins Data Science Specialization.

Learn how to gather, clean, and manage data from a variety of sources. This is the third course in the Johns Hopkins Data Science Specialization.

Learn the essential exploratory techniques for summarizing data. This is the fourth course in the Johns Hopkins Data Science Specialization.

Learn the concepts and tools behind reporting modern data analyses in a reproducible manner. This is the fifth course in the Johns Hopkins Data Science Specialization.

Learn how to draw conclusions about populations or scientific truths from data. This is the sixth course in the Johns Hopkins Data Science Course Track.

Learn how to use regression models, the most important statistical analysis tool in the data scientist's toolkit. This is the seventh course in the Johns Hopkins Data Science Specialization.

Learn the basic components of building and applying prediction functions with an emphasis on practical applications. This is the eighth course in the Johns Hopkins Data Science Specialization.

Learn the basics of creating data products using Shiny, R packages, and interactive graphics. This is the ninth course in the Johns Hopkins Data Science Specialization.

This course introduces the basic mathematical and programming principles that underlie much of Computer Science. Students will refine their programming skills as well as learn the basics of creating efficient solutions to common computational problems.

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems.

Learn about the technologies underlying experimentation used in systems biology, with particular focus on RNA sequencing, mass spec-based proteomics, flow/mass cytometry and live-cell imaging.

This course will focus on developing integrative skills through directed reading and analysis of the current primary literature to enable the student to develop the capstone project as the overall final exam for the specialization in systems biology.