Discover how to write elegant code that works the first time it is run.
This Specialization provides a hands-on introduction to functional programming using the widespread programming language, Scala. It begins from the basic building blocks of the functional paradigm, first showing how to use these blocks to solve small problems, before building up to combining these concepts to architect larger functional programs. You'll see how the functional paradigm facilitates parallel and distributed programming, and through a series of hands on examples and programming assignments, you'll learn how to analyze data sets small to large; from parallel programming on multicore architectures, to distributed programming on a cluster using Apache Spark. A final capstone project will allow you to apply the skills you learned by building a large data-intensive application using real-world data.
关于此 专项课程
您将学到的内容有
Write purely functional programs using recursion, pattern matching, and higher-order functions
Design immutable data structures
Write programs that effectively use parallel collections to achieve performance
Manipulate data with Spark and Scala
您将获得的技能
Scala ProgrammingParallel ComputingApache SparkFunctional Programming
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 5 门课程
课程1
Scala 函数式程序设计原理
4.8
5,887 个评分
Functional programming is becoming increasingly widespread in industry. This trend is driven by the adoption of Scala as the main programming language for many applications. Scala fuses functional and object-oriented programming in a practical package. It interoperates seamlessly with both Java and Javascript. Scala is the implementation language of many important frameworks, including Apache Spark, Kafka, and Akka. It provides the core infrastructure for sites such as Twitter, Tumblr and also Coursera.
In this course you will discover the elements of the functional programming style and learn how to apply them usefully in your daily programming tasks. You will also develop a solid foundation for reasoning about functional programs, by touching upon proofs of invariants and the tracing of execution symbolically.
The course is hands on; most units introduce short programs that serve as illustrations of important concepts and invite you to play with them, modifying and improving them. The course is complemented by a series programming projects as homework assignments.
Recommended background: You should have at least one year programming experience. Proficiency with Java or C# is ideal, but experience with other languages such as C/C++, Python, Javascript or Ruby is also sufficient. You should have some familiarity using the command line.
课程2
Functional Program Design in Scala
4.5
2,479 个评分
In this course you will learn how to apply the functional programming style in the design of larger applications. You'll get to know important new functional programming concepts, from lazy evaluation to structuring your libraries using monads. We'll work on larger and more involved examples, from state space exploration to random testing to discrete circuit simulators. You’ll also learn some best practices on how to write good Scala code in the real world.
Several parts of this course deal with the question how functional programming interacts with mutable state. We will explore the consequences of combining functions and state. We will also look at purely functional alternatives to mutable state, using infinite data structures or functional reactive programming.
Learning Outcomes. By the end of this course you will be able to:
- recognize and apply design principles of functional programs,
- design functional libraries and their APIs,
- competently combine functions and state in one program,
- understand reasoning techniques for programs that combine
functions and state,
- write simple functional reactive applications.
Recommended background: You should have at least one year programming experience. Proficiency with Java or C# is ideal, but experience with other languages such as C/C++, Python, Javascript or Ruby is also sufficient. You should have some familiarity using the command line. This course is intended to be taken after Functional Programming Principles in Scala: https://www.coursera.org/learn/progfun1.
课程3
并行编程
4.4
1,466 个评分
With every smartphone and computer now boasting multiple processors, the use of functional ideas to facilitate parallel programming is becoming increasingly widespread. In this course, you'll learn the fundamentals of parallel programming, from task parallelism to data parallelism. In particular, you'll see how many familiar ideas from functional programming map perfectly to to the data parallel paradigm. We'll start the nuts and bolts how to effectively parallelize familiar collections operations, and we'll build up to parallel collections, a production-ready data parallel collections library available in the Scala standard library. Throughout, we'll apply these concepts through several hands-on examples that analyze real-world data, such as popular algorithms like k-means clustering.
Learning Outcomes. By the end of this course you will be able to:
- reason about task and data parallel programs,
- express common algorithms in a functional style and solve them in parallel,
- competently microbenchmark parallel code,
- write programs that effectively use parallel collections to achieve performance
Recommended background: You should have at least one year programming experience. Proficiency with Java or C# is ideal, but experience with other languages such as C/C++, Python, Javascript or Ruby is also sufficient. You should have some familiarity using the command line. This course is intended to be taken after Functional Program Design in Scala: https://www.coursera.org/learn/progfun2.
课程4
Big Data Analysis with Scala and Spark
4.7
1,782 个评分
Manipulating big data distributed over a cluster using functional concepts is rampant in industry, and is arguably one of the first widespread industrial uses of functional ideas. This is evidenced by the popularity of MapReduce and Hadoop, and most recently Apache Spark, a fast, in-memory distributed collections framework written in Scala. In this course, we'll see how the data parallel paradigm can be extended to the distributed case, using Spark throughout. We'll cover Spark's programming model in detail, being careful to understand how and when it differs from familiar programming models, like shared-memory parallel collections or sequential Scala collections. Through hands-on examples in Spark and Scala, we'll learn when important issues related to distribution like latency and network communication should be considered and how they can be addressed effectively for improved performance.
Learning Outcomes. By the end of this course you will be able to:
- read data from persistent storage and load it into Apache Spark,
- manipulate data with Spark and Scala,
- express algorithms for data analysis in a functional style,
- recognize how to avoid shuffles and recomputation in Spark,
Recommended background: You should have at least one year programming experience. Proficiency with Java or C# is ideal, but experience with other languages such as C/C++, Python, Javascript or Ruby is also sufficient. You should have some familiarity using the command line. This course is intended to be taken after Parallel Programming: https://www.coursera.org/learn/parprog1.
讲师
Martin Odersky
ProfessorComputer Science
Prof. Viktor Kuncak
Associate ProfessorSchool of Computer and Communication Sciences
Dr. Julien Richard-Foy
Computer ScientistScala Center
Dr. Aleksandar Prokopec
Principal ResearcherOracle Labs
Dr. Heather Miller
Research ScientistEPFL
关于 洛桑联邦理工学院
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？
可以！点击您感兴趣的课程卡开始注册即可。注册并完成课程后，您可以获得可共享的证书，或者您也可以旁听该课程免费查看课程资料。如果您订阅的课程是某专项课程的一部分，系统会自动为您订阅完整的专项课程。访问您的学生面板，跟踪您的进度。
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？
此课程完全在线学习，无需到教室现场上课。您可以通过网络或移动设备随时随地访问课程视频、阅读材料和作业。
完成专项课程后我会获得大学学分吗？
此专项课程不提供大学学分，但部分大学可能会选择接受专项课程证书作为学分。查看您的合作院校了解详情。
How long does it take to complete the Functional Programming in Scala Specialization?
Time to completion can vary based on your schedule, but most learners are able to complete the Specialization in 4-5 months.
此专项课程中每门课程的开课频率为多久？
Each course in the Specialization is offered on demand, and may be taken at any time.
What background knowledge is necessary?
At least one year of programming experience is recommended. Proficiency with Java or C# is ideal, but experience with other languages such as C/C++, Python, JavaScript, or Ruby is also sufficient.
Do I have to take the courses in this Specialization in a specific order?
We recommend taking the courses in the order presented, as each subsequent course will build on material from previous courses.
Will I earn university credit for completing the Functional Programming in Scala Specialization?
Coursera courses and certificates don't carry university credit, though some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.
Are there any recommended readings for this specialization?
These courses are designed to be self-contained, however for further reading we recommend:(1) for a more thorough treatment of some of the ideas presented in the course: Structure and Interpretation of Computer Programs, 2nd Edition, by Harold Abelson,Gerald Jay Sussman //http://www.amazon.com/gp/product/0262011530?*Version*=1&*entries*=0...(2)for learning more about Scala: Programming in Scala: A Comprehensive Step-by-Step Guide, 2nd Edition, by Martin Odersky, Lex Spoon, Bill Venners // http://www.amazon.com/Programming-Scala-Comprehensive-Step-Step/dp/0981531644...(3)for learning more about Scala: Scala for the Impatient by Cay Horstmann // http://www.horstmann.com/scala/index.html...(4)for learning more about parallel and concurrent programming in Scala: Learning Concurrent Programming in Scala by Aleksandar Prokopec // http://www.amazon.com/Learning-Concurrent-Programming-Aleksandar-Prokopec/dp/1783281413...(5)for learning more about Spark: Learning Spark by Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia //http://shop.oreilly.com/product/0636920028512.do
还有其他问题吗？请访问 学生帮助中心。
