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.
Functional Programming in Scala Specialization
Program on a Higher Level. Write elegant functional code to analyze data that's big or small
Offered By
About this Specialization
What you will learn
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
Skills you will gain
Scala ProgrammingParallel ComputingApache SparkFunctional Programming
How the Specialization Works
Take Courses
A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.
Hands-on Project
Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.
Earn a Certificate
When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.
There are 5 Courses in this Specialization
Course1
Functional Programming Principles in Scala
4.8
6,096 ratings
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.
Course2
Functional Program Design in Scala
4.5
2,551 ratings
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.
Course3
Parallel programming
4.4
1,513 ratings
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.
Course4
Big Data Analysis with Scala and Spark
4.7
1,868 ratings
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.
Instructors
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
Prof. Heather Miller
Assistant ProfessorCarnegie Mellon University
About École Polytechnique Fédérale de Lausanne
Frequently Asked Questions
What is the refund policy?
Can I just enroll in a single course?
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
Is financial aid available?
Can I take the course for free?
Is this course really 100% online? Do I need to attend any classes in person?
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
Will I earn university credit for completing the Specialization?
This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.
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.
How often is each course in the Specialization offered?
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
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