Stanford University

 

 


 

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Jan 23rd 2017

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: 7.6 (29 votes)
Jan 23rd 2017

The primary topics in this part of the specialization are: shortest paths (Bellman-Ford, Floyd-Warshall, Johnson), NP-completeness and what it means for the algorithm designer, and strategies for coping with computationally intractable problems (analysis of heuristics, local search).

Average: 5 (2 votes)
Jan 23rd 2017

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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Jan 23rd 2017

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: 5.7 (13 votes)
Jan 23rd 2017

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.

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Jan 16th 2017

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)
Jan 16th 2017

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)
Jan 16th 2017

The primary topics in this part of the specialization are: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal search trees).

Average: 3 (2 votes)
Jan 16th 2017

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 (14 votes)
Jan 16th 2017

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)
Jan 9th 2017

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.

No votes yet
Jan 9th 2017

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.

Average: 1 (1 vote)
Jan 9th 2017

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)
Jan 2nd 2017

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)
Jan 2nd 2017

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)
Jan 2nd 2017

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)
Jan 2nd 2017

This course is an introduction to Logic from a computational perspective. It shows how to encode information in the form of logical sentences; it shows how to reason with information in this form; and it provides an overview of logic technology and its applications - in mathematics, science, engineering, business, law, and so forth.

Average: 8 (1 vote)
Dec 26th 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)
Dec 26th 2016

In this course you will learn about audio signal processing methodologies that are specific for music and of use in real applications. We focus on the spectral processing techniques of relevance for the description and transformation of sounds, developing the basic theoretical and practical knowledge with which to analyze, synthesize, transform and describe audio signals in the context of music applications.

No votes yet
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)

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