Online courses directory (684)

Solve problems using Mathematics, Computer Science and more!. Introduction. The Discovery. Clue #1. Clue #2. Clue #3. Crypto Checkpoint 1. Clue #4. Checkpoint. Crypto Checkpoint 2. Crypto Checkpoint 3. What's Next?. Introduction. The Discovery. Clue #1. Clue #2. Clue #3. Crypto Checkpoint 1. Clue #4. Checkpoint. Crypto Checkpoint 2. Crypto Checkpoint 3. What's Next?.

This Work, SI 615 - Seminar on Digital Libraries, by is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike license. This is a special topics seminar focusing on the current state of

This course provides a strong grounding in the economics of information goods and services. Students analyze strategic issues faced by for-profit and not-for-profit organizations: pricing, bundling, versioning, product differentiation and variety, network externalities, and rights management. This course precedes SI 680. Course Level: Graduate This Work, SI 646 - Information Economics, by Mark McCabe is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike license.

Infrastructure, Algorithms, and Visualizations

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.

Wildly popular due to its interactive multimedia capabilities, Java programming leads the list of Internet development skills in current commercial demand. This course is recommended for people who wish to become familiar with the principles of Java Programming. Through the use of hands-on exercises, students will explore the Java language fundamentals as well as basic concepts of object-oriented programming. At the end of this course, students will be able to:

This course will teach you the basics of Java Programming, still one of the most popular languages used.

Learn basic Java programming by developing a simple mobile game that you can run on your computer, Android phone, or tablet.

Introductory Machine Learning course covering theory, algorithms and applications. Our focus is on real understanding, not just "knowing."

This course covers functional, object-oriented, and declarative dataflow programming in a unified framework.

CS169.2x teaches sophisticated SaaS+Agile skills, such as working with legacy code, building on basics from CS169.1x.

In this course we’ll explore complex analysis, complex dynamics, and some applications of these topics.

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

Start learning how to program video games using the C# programming language. Plenty of practice opportunities are included!

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.

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.

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.

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.

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

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.