关于
Functional Programming in Scala 专项课程
第 1 门课程
Functional Programming Principles in Scala
第 2 门课程
Functional Program Design in Scala
第 3 门课程
Parallel programming
第 4 门课程
Big Data Analysis with Scala and Spark
第 5 门课程
Functional Programming in Scala Capstone
关于此专项课程

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.

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100% 在线课程

立即开始，按照自己的计划学习。
Intermediate Level

中级

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完成时间大约为5 个月

建议 5 小时/周
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您将学到的内容有

  • Check
    Describe the properties of functions
  • Check
    Design immutable data structures
  • Check
    Understand the principles of functional programming
  • Check
    write functional programs with recursion and pattern matching

您将获得的技能

Functional ProgrammingBig DataData StructureSql
Globe

100% 在线课程

立即开始，按照自己的计划学习。
Intermediate Level

中级

Clock

完成时间大约为5 个月

建议 5 小时/周
Comment Dots

English

字幕：English, Korean, Serbian, French

专项课程的运作方式

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how it works

此专项课程包含 5 门课程

1课程

Functional Programming Principles in Scala

4.8
5,124 个评分
•
1,067 个审阅
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. Learning Outcomes. By the end of this course you will be able to: - understand the principles of functional programming, - write purely functional programs, using recursion, pattern matching, and higher-order functions, - combine functional programming with objects and classes, - design immutable data structures, - reason about properties of functions, - understand generic types for functional programs 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....
2课程

Functional Program Design in Scala

4.5
2,178 个评分
•
391 个审阅
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....
3课程

Parallel programming

4.4
1,260 个评分
•
211 个审阅
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....
4课程

Big Data Analysis with Scala and Spark

4.7
1,477 个评分
•
326 个审阅
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....
5课程

Functional Programming in Scala Capstone

4.4
306 个评分
•
60 个审阅
In the final capstone project you will apply the skills you learned by building a large data-intensive application using real-world data. You will implement a complete application processing several gigabytes of data. This application will show interactive visualizations of the evolution of temperatures over time all over the world. The development of such an application will involve: — transforming data provided by weather stations into meaningful information like, for instance, the average temperature of each point of the globe over the last ten years ; — then, making images from this information by using spatial and linear interpolation techniques ; — finally, implementing how the user interface will react to users’ actions....

Instructors

Martin Odersky

Professor

Prof. Viktor Kuncak

Associate Professor

Dr. Julien Richard-Foy

Computer Scientist

Dr. Aleksandar Prokopec

Principal Researcher

Dr. Heather Miller

Research Scientist

关于 École Polytechnique Fédérale de Lausanne

常见问题

  • What is the refund policy?

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  • Can I take the course for free?

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  • Will I earn university credit for completing the Specialization?

  • How long does it take to complete the Functional Programming in Scala Specialization?

  • How often is each course in the Specialization offered?

  • What background knowledge is necessary?

  • Do I have to take the courses in this Specialization in a specific order?

  • Will I earn university credit for completing the Functional Programming in Scala Specialization?

  • Are there any recommended readings for this specialization?

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