Algorithms

 

 


 

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E.g., 2016-12-10
E.g., 2016-12-10
E.g., 2016-12-10
Dec 12th 2016

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems.

Average: 7.3 (8 votes)
Dec 12th 2016

How does Google Maps plan the best route for getting around town given current traffic conditions? How does an internet router forward packets of network traffic to minimize delay? How does an aid group allocate resources to its affiliated local partners? To solve such problems, we first represent the key pieces of data in a complex data structure. In this course, you’ll learn about data structures, like graphs, that are fundamental for working with structured real world data.

Average: 6.3 (12 votes)
Dec 12th 2016

This course will cover the major techniques for mining and analyzing text data to discover interesting patterns, extract useful knowledge, and support decision making, with an emphasis on statistical approaches that can be generally applied to arbitrary text data in any natural language with no or minimum human effort.

Average: 6.5 (2 votes)
Dec 12th 2016

Case Study - Predicting Housing Prices
In our first case study, predicting house prices, you will create models that predict a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,...). This is just one of the many places where regression can be applied. Other applications range from predicting health outcomes in medicine, stock prices in finance, and power usage in high-performance computing, to analyzing which regulators are important for gene expression.In this course, you will explore regularized linear regression models for the task of prediction and feature selection. You will be able to handle very large sets of features and select between models of various complexity. You will also analyze the impact of aspects of your data -- such as outliers -- on your selected models and predictions. To fit these models, you will implement optimization algorithms that scale to large datasets.

Average: 7.5 (4 votes)
Dec 12th 2016

How do Java programs deal with vast quantities of data? Many of the data structures and algorithms that work with introductory toy examples break when applications process real, large data sets. Efficiency is critical, but how do we achieve it, and how do we even measure it? In this course, you will use and analyze data structures that are used in industry-level applications, such as linked lists, trees, and hashtables.

Average: 6.3 (4 votes)
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

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation.

Average: 6 (15 votes)
Dec 12th 2016

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems.

Average: 6 (6 votes)
Dec 12th 2016

The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming. We will learn a lot of theory: how to sort data and how it helps for searching; how to break a large problem into pieces and solve them recursively; when it makes sense to proceed greedily; how dynamic programming is used in genomic studies. You will practice solving computational problems, designing new algorithms, and implementing solutions efficiently (so that they run in less than a second).

Average: 7.4 (9 votes)
Dec 12th 2016

本课程内容程涵盖枚举、二分、贪心、递归、深度优先搜索、广度优先搜索、动态规划等基本算法。通过大量的高强度的编程训练,提高动手能力,做到能较为熟练、完整、准确地实现自己设计的程序,为进一步学习其他计算机专业课程,或在其他专业领域运用计算机编程解决问题奠定良好的基础。

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Dec 12th 2016

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.

Average: 4 (2 votes)
Dec 12th 2016

A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. In this course, we consider the common data structures that are used in various computational problems. You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments.

Average: 9 (4 votes)
Dec 12th 2016

Cloud computing systems today, whether open-source or used inside companies, are built using a common set of core techniques, algorithms, and design philosophies—all centered around distributed systems. Learn about such fundamental distributed computing "concepts" for cloud computing.

Average: 8 (2 votes)
Dec 12th 2016

本课程的目的有二:其一,帮助同学们了解计算机的基本运行原理,了解程序运行的基本原理,了解计算机的发展状态及趋势。其二,引导同学们逐步进入"计算机程序设计语言"的学习。我们希望本课程为同学们解答如下一些问题:计算机为什么能够进行计算?计算机程序是怎样运行的?计算机未来可能的发展趋势有哪些?程序是如何编写出来的?如何学习程序设计语言?程序设计语言的基本成分有哪些? 完成本课程,表明同学们已经了解了计算机运行的基本原理,了解了计算机程序的基本特性。

Average: 1 (1 vote)
Dec 12th 2016

If you have ever used a navigation service to find optimal route and estimate time to destination, you've used algorithms on graphs. Graphs arise in various real-world situations as there are road networks, computer networks and, most recently, social networks! If you're looking for the fastest time to get to work, cheapest way to connect set of computers into a network or efficient algorithm to automatically find communities and opinion leaders in Facebook, you're going to work with graphs and algorithms on graphs.

Average: 6.7 (7 votes)
Dec 12th 2016

这门课程将帮助学生学习如何运用高级的数据结构和相关算法解决复杂的应用问题。

Average: 3 (1 vote)
Dec 12th 2016

In this course, you will learn the fundamental techniques for making personalized recommendations through nearest-neighbor techniques. First you will learn user-user collaborative filtering, an algorithm that identifies other people with similar tastes to a target user and combines their ratings to make recommendations for that user.

Average: 6.5 (2 votes)
Dec 12th 2016

World and internet is full of textual information. We search for information using textual queries, we read websites, books, e-mails. All those are strings from the point of view of computer science. To make sense of all that information and make search efficient, search engines use many string algorithms. Moreover, the emerging field of personalized medicine uses many search algorithms to find disease-causing mutations in the human genome.

Average: 6.4 (10 votes)
Dec 12th 2016

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.

Average: 9 (2 votes)
Dec 12th 2016

这门课程将帮助学生学习如何运用基础的数据结构和相关算法解决实际应用问题。

Average: 4.5 (2 votes)

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