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 functiol 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 programsRecommended 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.

Learn the latest Big Data technology - Spark and Scala, including Spark 2.0 DataFrames!

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.

Note: Learning Scala Web Development was created by Packt Publishing. It was originally released on 5/30/2016. We are pleased to host this training in our library.

Embark on an exciting journey into the universe of web development using the Scala programming language and frameworks- "natural choices for back-end developers building highly scalable, reliable, and reactive RESTful web services and APIs. This training is the starting point for mastering the nonblocking and asynchronous programming models that lie in the heart of the Spray framework. It starts with an introduction to the REST architecture. Then switch gears to the Akka toolkit and framework, building a sample book catalog application along the way.

Once you've learned about the REST architectural style and Actor model- "the foundations that the Spray framework is built upon- "you'll shape out your own RESTful web services by providing simple route definitions. Further on in the course, author Andriy Redko delves into authentication and authorization, secure transport, documentation, testing, and caching support. Finally, you will learn how to develop the Spray client API to call external web services.

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 mods. 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 altertives 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.

Principles of Reactive Programming in Scala.

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 alysis in a functiol 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.

A must-have for Akka developers: write long-term reactive systems with Akka Persistence and PostgreSQL or Cassandra!

Integrate ElasticSearch with Java, Python, and Scala, and use Plugins to extend its usefulness.