Few people who “just Google it” to find an answer to their every question understand just what the company does (and why). Through this course, you'll join the minority that really gets it.
This course is an introduction to information theory, which emphasizes fundamental concepts as well as analytical techniques. Specific topics include: Information Measures, The I-Measure, Zero-Error Data Compression, Weak Typicality, Strong Typicality, Discrete Memoryless Channels, etc.
Programming-oriented course on effectively using modern computers to solve scientific computing problems arising in the physical/engineering sciences and other fields. Provides an introduction to efficient serial and parallel computing using Fortran 90, OpenMP, MPI, and Python, and software development tools such as version control, Makefiles, and debugging.
Modéliser un problème, concevoir un algorithme de résolution et en proposer une implémentation correcte. Du problème à sa solution, ce cours combine approches pragmatique, pratique et théorique de l'informatique.
This course serves as an introduction to the basic principles that govern all aspects of our networked lives. We will learn about companies like Google and technologies like the Internet in a way that requires no mathematics beyond basic algebra.
This course introduces the concepts, applications, algorithms, programming, and design of recommender systems--software systems that recommend products or information, often based on extensive personalization. Learn how web merchants such as Amazon.com personalize product suggestions and how to apply the same techniques in your own systems!
Education is increasingly occurring online or in educational software,
resulting in an explosion of data
that can be used to improve educational effectiveness and
support basic research on learning. In this course, you will learn how
and when to use key methods for educational data mining and
learning analytics on this data.
Learn how to build and deploy modern web application architectures – applications that run over the Internet, in the "cloud," using a browser as the user interface.
Use of available (mainly web-based) programs for analyzing biological data. This is Part 2 of 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.
This course teaches the concepts and computational methods in the exciting interdisciplinary field of bioinformatics and their applications in life sciences. The lectures are taught in both Mandarin Chinese and English with slides in English.
生物信息学是一门新兴的生命科学与计算科学的前沿交叉学科。本课程讲授生物信息学主要概念和方法,以及如何应用生物信息学手段解决生命科学问题。本课程同时提供中文普通话授课和英文授课两个版本,以及英文幻灯片。
This course teaches a calculus that enables precise quantitative predictions of large combinatorial structures. In addition, this course covers generating functions and real asymptotics and then introduces the symbolic method in the context of applications in the analysis of algorithms and basic structures such as permutations, trees, strings, words, and mappings.
We will present the state of the art energy minimization algorithms that are used to perform inference in modern artificial vision models: that is, efficient methods for obtaining the most likely interpretation of a given visual input. We will also cover the popular max-margin framework for estimating the model parameters using inference.
The Coursera course, Data Analysis and Statistical Inference has been revised and is now offered as part of Coursera Specialization “Statistics with R”.
This course introduces you to the discipline of statistics as a science of understanding and analyzing data. You will learn how to effectively make use of data in the face of uncertainty: how to collect data, how to analyze data, and how to use data to make inferences and conclusions about real world phenomena.
Computer haben unser Leben tiefgreifend verändert. Um die heutige Gesellschaft und Wirtschaft und deren stetigen Veränderungen zu verstehen, muss man wissen, wie Computer funktionieren.
Das Ziel der Vorlesung Informatik für Ökonomen ist es, Ihnen eine Basis zu vermitteln, um unsere informationstechnisch gesteuerte Welt zu verstehen und darin erfolgreich zu sein.
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