MOOC

Information, Computation, Communication: Introduction to computational thinking

Description

In the first part of the course, we'll look at how algorithms can be used to solve a problem in a very concrete way, leading us on to one of the great questions of modern theoretical computer science.

The second part of the course will be devoted to information and communication: we'll be looking at a number of topics, including information representation, signal processing, data compression, communication and cryptography.

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Description

Instructor

Olivier Lévêque

Olivier Lévêque was born in Switzerland in 1971. He received the physics diploma from EPFL in 1995 and completed his PhD in mathematics at EPFL in 2001. Since then, he has been with the Laboratory of Information Theory at EPFL. He spent the academical year 2005-2006 at the Electrical Engineering Department of Stanford University, where he was appointed as lecturer. His research interests include stochastic analysis, random matrices, wireless communications and information theory.

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Lectures in this MOOC (37)

Complexity Classes: Introduction and Examples MOOC: Information, Computation, Communication: Introduction to computational thinking

Introduces complexity classes, including P and NP, and explores examples of easy and hard problems.

Sampling Theorem MOOC: Information, Computation, Communication: Introduction to computational thinking

Explores the sampling theorem, illustrating signal reconstruction and the importance of meeting the Nyquist criterion.

Entropy: Examples and Properties MOOC: Information, Computation, Communication: Introduction to computational thinking

Explores examples of guessing letters, origins of entropy, and properties in information theory.

Lossless Compression: Shannon-Fano and Huffman MOOC: Information, Computation, Communication: Introduction to computational thinking

Explores lossless compression using Shannon-Fano and Huffman algorithms, showcasing Huffman's superior efficiency and speed over Shannon-Fano.

Binary Representation of Real Numbers MOOC: Information, Computation, Communication: Introduction to computational thinking

Discusses the binary representation of real numbers and the precision errors involved.

Related concepts (32)

Communication studies

Communication studies or communication science is an academic discipline that deals with processes of human communication and behavior, patterns of communication in interpersonal relationships, social interactions and communication in different cultures. Communication is commonly defined as giving, receiving or exchanging ideas, information, signals or messages through appropriate media, enabling individuals or groups to persuade, to seek information, to give information or to express emotions effectively.

Media (communication)

In mass communication, media are the communication outlets or tools used to store and deliver information or data. The term refers to components of the mass media communications industry, such as print media, publishing, the news media, photography, cinema, broadcasting (radio and television), digital media, and advertising. The development of early writing and paper enabling longer-distance communication systems such as mail, including in the Persian Empire (Chapar Khaneh and Angarium) and Roman Empire, can be interpreted as early forms of media.

Information Age

The Information Age (also known as the Computer Age, Digital Age, Silicon Age, New Media Age, or Media Age) is a historical period that began in the mid-20th century. It is characterized by a rapid shift from traditional industries, as established during the Industrial Revolution, to an economy centered on information technology. The onset of the Information Age has been linked to the development of the transistor in 1947, the optical amplifier in 1957, and Unix time, which began on January 1, 1970.