The latest addition to Coursera's list of Computer Science Specializations is a hands-on introduction to functional programming using the widespread programming language, Scala. The first and third of the courses it consists of open today.

Although this Specialization, which consists of four 4 to 6 week courses followed by a Capstone project is being launched today, its first course, made its first appearance in March 2013. On the basis of enthusiastic reviews from students on its two presentations it ranks #2 in Computer Science on Class Central. The reason it is so highly regarded is the one Coursera is using to promote the new Specialization - it is taught by a team from EPFL (École Polytechnique Fédérale de Lausanne) which includes the creator of Scala, Martin Odersky who is a professor there. Odersky himself teaches the first two courses in the Specialization.

According to its description:

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.

•  Principles of Functional Programming: Recursion, pattern matching, higher-order functions, and immutable data structures

•  Functional Program Design: Design principles, functional libraries and APIs, and functional reactive programs

•  Parallel Programming: Task and data parallel programs, microbenchmarking parallel code, and using parallel collections to achieve performance

•  Big Data Analysis: Read data load it into Apache Spark, manipulate data with Spark and Scala, and express algorithms for data analysis in a functional style

•  Capstone Project: Build a large, data-intensive application using real-world data

The first course in the series, which starts today and, now it is part of a specialization can be expected to start again in a few weeks time is Functional Programming Principles in Scala, which assumes prior programming knowledge and is hand-on. Its six weekly units introduce short programs that serve as illustrations of important concepts which students will modify and improve and assignments will mostly consist of programming projects.

The second course, Functional Program Design in Scala, taught by the creator of Scala, Martin Odersky who is also a professor at EPFL (École Polytechnique Fédérale de Lausanne). This course assumes prior programming knowledge and is hand-on. Its 7 weekly units introduce short programs that serve as illustrations of important concepts which students will modify and improve and assignments will mostly consist of programming projects.also taught by Odersky has an upcoming session starting June 20th and has four units.

Parallel Programming also starts today and shows how many familiar ideas from functional programming map perfectly to to the data parallel paradigm. In the first week of the four week course students will be introduced to  the basic constructs for building parallel programs on JVM and Scala. 

The final course Big Data Analysis with Scala and Spark, billed as coming soon, will looks at how the data parallel paradigm can be extended to the distributed case, using Spark throughout.

With functional programming becoming increasingly widespread in industry and the way in which Scala fuses functional and object-oriented programming, this specialization seems to be a good addition to Coursera's growing list.

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More Information

Functional Programming in Scala Specialization

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