Online courses directory (147)

This Capstone MOOC gives Signature Track students who passed all previous MOOCs in the MoCCA Specialization “with Distinction” an opportunity to integrate and demonstrate the knowledge they've acquired across the three earlier content area MOOCs.

本課程有兩大課程目標： 1. 使同學了解如何以搜尋達成人工智慧 2. 使同學能將相關技術應用到自己的問題上

Use of available (mainly web-based) programs for analyzing biological data. This is an introductory course with a strong emphasis on hands-on methods. Some theory is introduced, but the main focus is on using extant bioinformatics tools to analyze data and generate biological hypotheses.

LaTeX (читается «латех») — научная издательская система. На этом курсе вы узнаете, как оформить ваши идеи в виде красивого, профессионально сверстанного текста или слайдов презентации. LaTeX ('lay-tech') is a desktop publishing system for academic publications. Learn how to put your research into professionally looking form of a printed text or presentation slides.

Learn both theory and application for basic methods that have been invented either for developing new concepts – principal components or clusters, or for finding interesting correlations – regression and classification. This is preceded by a thorough analysis of 1D and 2D data.

El curso es bilingüe español-inglés, con videos y materiales en ambos idiomas. Lectures and materials are provided both in Spanish and English.

In this 5-week course we’ll introduce the fundamentals of programming in Processing, an accessible introduction to combining arts and computing. The course will provide the essentials of programming in a visual context, allowing you to visualize, design, and create generative art with Processing.

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 .

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.

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 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.

This course focuses on how to design and build secure systems with a human-centric focus. We will look at basic principles of human-computer interaction, and apply these insights to the design of secure systems with the goal of developing security measures that respect human performance and their goals within a system.

This course we will explore the foundations of software security. We will consider important software vulnerabilities and attacks that exploit them -- such as buffer overflows, SQL injection, and session hijacking -- and we will consider defenses that prevent or mitigate these attacks, including advanced testing and program analysis techniques. Importantly, we take a "build security in" mentality, considering techniques at each phase of the development cycle that can be used to strengthen the security of software systems.