- Debugging
- Software Testing
- Algorithms
- Data Structure
- Computer Programming
- Dynamic Programming
- Binary Search Tree
- Priority Queue
- Hash Table
- Stack (Abstract Data Type)
- List
- Graph Theory

# 数据结构与算法 专项课程

掌握算法编程技术. Advance your Software Engineering or Data Science Career by Learning Algorithms through Programming and Puzzle Solving. Ace coding interviews by implementing each algorithmic challenge in this Specialization. Apply the newly-learned algorithmic techniques to real-life problems, such as analyzing a huge social network or sequencing a genome of a deadly pathogen.

**286,155**人已注册

提供方

## 您将学到的内容有

Play with 50 algorithmic puzzles on your smartphone to develop your algorithmic intuition! Apply algorithmic techniques (greedy algorithms, binary search, dynamic programming, etc.) and data structures (stacks, queues, trees, graphs, etc.) to solve 100 programming challenges that often appear at interviews at high-tech companies. Get an instant feedback on whether your solution is correct.

Apply the newly learned algorithms to solve real-world challenges: navigating in a Big Network or assembling a genome of a deadly pathogen from millions of short substrings of its DNA.

Learn exactly the same material as undergraduate students in “Algorithms 101” at top universities and more! We are excited that students from various parts of the world are now studying our online materials in the Algorithms 101 classes at their universities. Here is a quote from the website of Professor Sauleh Eetemadi from Iran University of Science and Technology: “After examining syllabus and course material from top universities including Stanford, Princeton and MIT we have chosen to follow the Data Structures and Algorithms Specialization from UCSD...due to excellent course material and its practical approach.”

If you decide to venture beyond Algorithms 101, try to solve more complex programming challenges (flows in networks, linear programming, streaming algorithms, etc.) and complete an equivalent of a graduate course in algorithms!

## 您将获得的技能

## 关于此 专项课程

## 应用的学习项目

The specialization contains two real-world projects: Big Networks and Genome Assembly. You will analyze both road networks and social networks and will learn how to compute the shortest route between New York and San Francisco 1000 times faster than the shortest path algorithms you learn in the standard Algorithms 101 course! Afterwards, you will learn how to assemble genomes from millions of short fragments of DNA and how assembly algorithms fuel recent developments in personalized medicine.

Basic knowledge of at least one programming language: C++, Java, Python, C, C#, Javascript, Haskell, Kotlin, Ruby, Rust, Scala. Basic knowledge of discrete mathematics: proof by induction, proof by contradiction.

Basic knowledge of at least one programming language: C++, Java, Python, C, C#, Javascript, Haskell, Kotlin, Ruby, Rust, Scala. Basic knowledge of discrete mathematics: proof by induction, proof by contradiction.

## 专项课程的运作方式

### 加入课程

Coursera 专项课程是帮助您掌握一门技能的一系列课程。若要开始学习，请直接注册专项课程，或预览专项课程并选择您要首先开始学习的课程。当您订阅专项课程的部分课程时，您将自动订阅整个专项课程。您可以只完成一门课程，您可以随时暂停学习或结束订阅。访问您的学生面板，跟踪您的课程注册情况和进度。

### 实践项目

每个专项课程都包括实践项目。您需要成功完成这个（些）项目才能完成专项课程并获得证书。如果专项课程中包括单独的实践项目课程，则需要在开始之前完成其他所有课程。

### 获得证书

在结束每门课程并完成实践项目之后，您会获得一个证书，您可以向您的潜在雇主展示该证书并在您的职业社交网络中分享。

## 此专项课程包含 6 门课程

### Algorithmic Toolbox

This online 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).

### 数据结构

A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. In this online 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. This will help you to understand what is going on inside a particular built-in implementation of a data structure and what to expect from it. You will also learn typical use cases for these data structures.

### Algorithms on Graphs

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 a 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.

### 字符串算法

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. In this online course you will learn key pattern matching concepts: tries, suffix trees, suffix arrays and even the Burrows-Wheeler transform.

## 提供方

### 加州大学圣地亚哥分校

UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.

## 常见问题

退款政策是如何规定的？

我可以只注册一门课程吗？

有助学金吗？

我可以免费学习课程吗？

此课程是 100% 在线学习吗？是否需要现场参加课程？

What will I be able to do upon completing the Specialization?

What background knowledge is necessary?

What is the difference between this course and other courses covering algorithms?

完成专项课程需要多长时间？

此专项课程中每门课程的开课频率为多久？

What background knowledge is necessary?

Do I need to take the courses in a specific order?

完成专项课程后我会获得大学学分吗？

Do I need to buy a textbook for this specialization?

还有其他问题吗？请访问 学生帮助中心。