Courses tagged with "Evaluation" (733)

Investigate the basic concepts behind programming languages, with an emphasis on the techniques and benefits of functional programming. Use the programming languages ML, Racket, and Ruby to learn how the pieces of a language fit together to create more than the sum of the parts. Gain new software skills and the concepts needed to learn new languages on your own.

CS101 teaches the essential ideas of Computer Science for a zero-prior-experience audience. The course uses small coding experiments in the browser to play with the nature of computers, understanding their strengths and limitations. Sign up for the "To be announced" session to be notified by email when the class is next run, and sign up for "Self-Study" to start browsing the class materials right away. Self-Study mode makes all the videos and assignments available to be done at your own pace, but without a certificate of completion at the end.

This course is about learning to program well: building programs that are elegant, well tested and easy to maintain. The course is designed for students with no programming experience at all. Nonetheless, former students who already knew how to program have said it made them better programmers.

In this course, you will explore several structured, risk management approaches that guide information security decision-making. 

Quantum computation is a remarkable subject building on the great computational discovery that computers based on quantum mechanics are exponentially powerful. This course aims to make this cutting-edge material broadly accessible to undergraduate students, including computer science majors who do not have any prior exposure to quantum mechanics. The course starts with a simple introduction to the fundamental principles of quantum mechanics using the concepts of qubits (or quantum bits) and quantum gates. This treatment emphasizes the paradoxical nature of the subject, including entanglement, non-local correlations, the no-cloning theorem and quantum teleportation. The course covers the fundamentals of quantum algorithms, including the quantum fourier transform, period finding, Shor's quantum algorithm for factoring integers, as well as the prospects for quantum algorithms for NP-complete problems. It also discusses the basic ideas behind the experimental realization of quantum computers, including the prospects for adiabatic quantum optimization and the D-Wave controversy.

Before your course starts, try the new edX Demo where you can explore the fun, interactive learning environment and virtual labs. Learn more.

Do I need a textbook for this class?
No. Notes will be posted each week. If you wish to consult other references, a list of related textbooks and online resources will be provided.

What is the estimated effort for course?
About 5-12 hrs/week.

Why is the work load range so wide?
How long you spend on the course depends upon your background and on the depth to which you wish to understand the material. The topics in this course are quite open ended, and will be presented so you can understand them at a high level or can try to follow it at a sophisticated level with the help of the posted notes.

How much does it cost to take the course?
Nothing! The course is free.

Will the text of the lectures be available?
Yes. All of our lectures will have transcripts synced to the videos.

Do I need to watch the lectures live?
No. You can watch the lectures at your leisure.

Learn to defend and protect vital company information using the latest technology and defense strategies. Analyze internal and external threats to proactively prevent information attacks. Gain experience by solving real-world problems and leave the class equipped to establish and oversee information security.

Learn the engineering skills needed to build a technology startup from the ground up.

This course provides you with opportunities to integrate and apply your information security knowledge.

This course was the first in a two-part series covering some of the algorithms underlying bioinformatics. It has now been split into three smaller courses.

We live in a time of unprecedented access to information. You'll learn how to use statistics to interpret that information and make decisions. San Jose State University

This cross-disciplinary course deals with the undetermined, the unpredictable- or what appears to be such. Learn about the usefulness of randomness in communication and computation, the intrinsic randomness of quantum phenomena, the unpredictability of the weather, and the implications of the neural activity of the brain on our "free will".

Ce cours initie à la programmation en utilisant le langage C++. Il ne présuppose pas de connaissance préalable. Les aspects plus avancés (programmation orientée objet) sont donnés dans un cours suivant, «Introduction à la programmation orientée objet (en C++)».

This course is for experienced C programmers who want to program in C++. The examples and exercises require a basic understanding of algorithms and object-oriented software.

Dieser Kurs vermittelt einen Überblick über die Grundlagen des Maschinellen Sehens an Hand der Extraktion von 3D-Information aus dem Stereokamerabild einer Szene.

Ce cours initie à la programmation en utilisant le langage Java. Il ne présuppose pas de connaissance préalable. Les aspects plus avancés (programmation orientée objet) sont donnés dans un cours suivant, «Introduction à la programmation orientée objet (en Java)».

Ce cours introduit la programmation orientée objet en l'illustrant en langage C++. Il présuppose connues les bases de la programmation (variables, types, boucles, fonctions, ...). Il est conçu comme la suite du cours «Initiation à la programmation (en C++)».

This course provides a complete introduction to programming for digital musicians and artists, in the real-time multimedia language ChucK. Rich with practical examples and pointers to additional web resources, it can be understood by novices wishing to learn to program interactive arts systems.

Let’s make history together - again! 让我们再一次创造历史！

Learn how to model social and economic networks and their impact on human behavior. How do networks form, why do they exhibit certain patterns, and how does their structure impact diffusion, learning, and other behaviors? We will bring together models and techniques from economics, sociology, math, physics, statistics and computer science to answer these questions.