Online courses directory (147)

Learn how to write composable software that stays responsive at all times by being elastic under load and resilient in the presence of failures. Model systems after human organizations or inter-human communication.

学习运用计算思维分析社会学、经济学问题的方法，加深对某些生活现象的理解，体会计算与社会科学的互动。 Learn to analyze and reason about problems in social sciences with computational thinking, appreciate interactions between computing and social sciences, as well as gain deeper understanding of some common phenomena in life and society

“数据结构与算法”是计算机学科中的核心基础课程。课程的主要目标培养学生较全面地理解基本数据结构的概念和经典算法的思想及各种实现方法，掌握数据结构和算法的设计分析技术。根据所求解问题的性质选择合理的数据结构并对时间空间复杂性进行必要的控制，提高程序设计的质量。使得学生在将来的学习、研究和工作中，具备设计和实现高效的数据结构和算法的能力。

In this course you will learn a whole lot of modern physics (classical and quantum) from basic computer programs that you will download, generalize, or write from scratch, discuss, and then hand in. Join in if you are curious (but not necessarily knowledgeable) about algorithms, and about the deep insights into science that you can obtain by the algorithmic approach.

Machine learning is the study that allows computers to adaptively improve their performance with experience accumulated from the data observed. The course teaches the most fundamental algorithmic, theoretical and practical tools that any user of machine learning needs to know. [機器學習旨在讓電腦能由資料中累積的經驗來自我進步。本課程將介紹各領域中的機器學習使用者都應該知道的基礎演算法、理論及實務工具。]

Learn various methods of analysis including: unsupervised clustering, gene-set enrichment analyses, Bayesian integration, network visualization, and supervised machine learning applications to LINCS data and other relevant Big Data from high content molecular and phenotype profiling of human cells.

The network is what makes the cloud. The cloud’s key capabilities—the ability to share infrastructure, the ability to move and scale applications across servers, massive parallelism, virtualization, and worldwide connectivity—are all rooted in the network. Learn how it all works!

Learn how to take scattered data and organize it into groups for use in many applications, such as market analysis and biomedical data analysis, or as a pre-processing step for many data mining tasks.

Learn how to transform information from a format efficient for computation into a format efficient for human perception, cognition, and communication. Explore elements of computer graphics, human-computer interaction, perceptual psychology, and design in addition to data processing and computation.

Learn how to use the cloud and write programs for data analytics.

本課程教授BIM技術的基礎知識，並以貼近實務之工程案例為教學範例，教授BIM塑模之基礎觀念與操作邏輯，並讓學生能實際應用BIM工具於案例實作中。

本課程教授BIM技術應用的基本知識及發展潛力，重點放在如何應用BIM資訊模型於實務工程中，包括設計衝突之檢討、工程數量之估算、工程進度之管理等應用。

Have you ever wished you knew how to program, but had no idea where to start from? This course will teach you how to program in Scratch, an easy to use visual programming language. More importantly, it will introduce you to the fundamental principles of computing and it will help you think like a software engineer.

讲授C++语言中和面向对象有关的概念和语法，如类和对象、运算符重载、继承和多态、类模板和算法模板、标准模板库等。目标是使得学生能够用C++语言，以面向对象的方法编写可维护性、可扩充性好的，较大规模的程序，初步领会面向对象程序设计方法的优势所在。

本课程的目的有二：其一，学知识，向大家传授关于C程序设计语言的基本知识；其二，练技能，培养使用C语言编写计算机程序解决实际问题的能力。通过本课程的训练，我们希望大家能够理解“结构化程序设计的基本思想”，掌握“C程序设计的基本技巧”，养成“良好的编程习惯和编程风格”，编写出“真正具有生命力的计算机程序”。 完成本课程，表明同学们已经掌握了“C程序设计的基本技能”，并具有“合乎规范的编程习惯”。

¿Alguna vez pensaste en crear tus propios juegos de computadora, pero no tenías idea cómo hacerlo o por dónde comenzar? Este curso te enseñará a programar utilizando Scratch, un lenguaje de programación visual muy fácil de usar, y más importante aún, aprenderás los principios fundamentales de la computación para que comiences a pensar como ingeniero/a de software.

Learn core distributed computing concepts that underlie today’s and tomorrow’s cloud computing systems.

This is the second course in a two-part series on bioinformatics algorithms, covering the following topics: evolutionary tree reconstruction, applications of combinatorial pattern matching for read mapping, gene regulatory analysis, protein classification, computational proteomics, and computational aspects of human genetics.

Are you interested in learning how to program (in Python) within a scientific setting? This course will cover algorithms for solving various biological problems along with a handful of programming challenges helping you implement these algorithms in Python. It offers a gentler-paced alternative to the first course in our Bioinformatics Specialization (Finding Hidden Messages in DNA).