Stanford University

 

 


 

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Dec 12th 2016

Learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome.

Average: 7.8 (26 votes)
Dec 12th 2016

In this course we will seek to “understand Einstein,” especially focusing on the special theory of relativity that Albert Einstein, as a twenty-six year old patent clerk, introduced in his “miracle year” of 1905. Our goal will be to go behind the myth-making and beyond the popularized presentations of relativity in order to gain a deeper understanding of both Einstein the person and the concepts, predictions, and strange paradoxes of his theory.

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Dec 5th 2016

The primary topics in this part of the specialization are: asymptotic ("Big-oh") notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts).

Average: 6.5 (2 votes)
Dec 5th 2016

The primary topics in this part of the specialization are: data structures (heaps, balanced search trees, hash tables, bloom filters), graph primitives (applications of breadth-first and depth-first search, connectivity, shortest paths), and their applications (ranging from deduplication to social network analysis).

Average: 5 (1 vote)
Dec 5th 2016

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.

Average: 10 (1 vote)
Dec 5th 2016

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. They are the basis for the state-of-the-art methods in a wide variety of applications, such as medical diagnosis, image understanding, speech recognition, natural language processing, and many, many more. They are also a foundational tool in formulating many machine learning problems.

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Dec 5th 2016

In this introductory, self-paced course, you will learn multiple theories of organizational behavior and apply them to actual cases of organizational change. Organizations are groups whose members coordinate their behaviors in order to accomplish a shared goal. They can be found nearly everywhere in today’s society: universities, start-ups, classrooms, hospitals, non-profits, government bureaus, corporations, restaurants, grocery stores, and professional associations are some of many examples of organizations.

Average: 6.5 (12 votes)
Dec 5th 2016

Popularized by movies such as "A Beautiful Mind," game theory is the mathematical modeling of strategic interaction among rational (and irrational) agents. Beyond what we call `games' in common language, such as chess, poker, soccer, etc., it includes the modeling of conflict among nations, political campaigns, competition among firms, and trading behavior in markets such as the NYSE.

Average: 5 (3 votes)
Nov 28th 2016

Cryptography is an indispensable tool for protecting information in computer systems. In this course you will learn the inner workings of cryptographic systems and how to correctly use them in real-world applications. The course begins with a detailed discussion of how two parties who have a shared secret key can communicate securely when a powerful adversary eavesdrops and tampers with traffic.

Average: 4.9 (11 votes)
Nov 28th 2016

A philanthropist is anyone who gives anything — time, money, experience, skills, and networks — in any amount, to create a better world. This course will empower you to become a more effective philanthropist and make your giving more meaningful to both you and those you strive to help.

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Nov 21st 2016

In this course, learners will be given the information and practical skills they need to begin optimizing the way they eat. This course will shift the focus away from reductionist discussions about nutrients and move, instead, towards practical discussions about real food and the environment in which we consume it.

Average: 6.8 (11 votes)
Nov 21st 2016

Eating patterns that begin in childhood affect health and well-being across the lifespan. The culture of eating has changed significantly in recent decades, especially in parts of the world where processed foods dominate our dietary intake. This course examines contemporary child nutrition and the impact of the individual decisions made by each family.

Average: 7.8 (13 votes)
Nov 21st 2016

About this course: Popularized by movies such as "A Beautiful Mind", game theory is the mathematical modeling of strategic interaction among rational (and irrational) agents. Over four weeks of lectures, this advanced course considers how to design interactions between agents in order to achieve good social outcomes. Three main topics are covered: social choice theory (i.e., collective decision making and voting systems), mechanism design, and auctions.

Average: 6 (4 votes)
Oct 4th 2016

Today's vast amount of streaming and video conferencing on the Internet lacks one aspect of musical fun and that's what this course is about: high-quality, near-synchronous musical collaboration. Under the right conditions, the Internet can be used for ultra-low-latency, uncompressed sound transmission. The course teaches open-source (free) techniques for setting up city-to-city studio-to-studio audio links. Distributed rehearsing, production and split ensemble concerts are the goal. Setting up such links and debugging them requires knowledge of network protocols, network audio issues and some ear training.

Average: 6 (2 votes)
Oct 3rd 2016

In this course you will learn several fundamental principles of algorithm design: divide-and-conquer methods, graph algorithms, practical data structures, randomized algorithms, and more.

Average: 6.4 (5 votes)
Oct 3rd 2016

Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This course is an introduction to algorithms for learners with at least a little programming experience. The course is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. After completing this course, you will have a greater mastery of algorithms than almost anyone without a graduate degree in the subject.

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Sep 26th 2016

In this course you will learn about audio signal processing methodologies that are specific for music and of use in real applications. You will learn to analyse, synthesize and transform sounds using the Python programming language.

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Sep 20th 2016

This course introduces the basics of Digital Signal Processing and computational acoustics, motivated by the vibrational physics of real-world objects and systems. We will build from a simple mass-spring and pendulum to demonstrate oscillation, how to simulate those systems in the computer, and also prove that simple oscillation behaves as a sine wave. From that we move to plucked strings and struck bars, showing both solutions as combined traveling waves and combined sine wave harmonics.

Average: 7.6 (13 votes)
Aug 2nd 2016

Careers in Media Technology explores how leading audio, music, and video technology companies, such as Sonos, Adobe, Smule, Dolby, iZotope, Universal Audio, and Avid, bring products from idea to market.

Average: 10 (2 votes)
Jul 5th 2016

TE introduces the fundamentals of technology entrepreneurship pioneered in Silicon Valley and now spreading globally. This is an online course where participants are learning in teams, and practicing entrepreneurship through concrete projects, some of which have become real startups.

Average: 8 (3 votes)

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