Parallel, concurrent, and distributed programming underlies software in multiple domains, ranging from biomedical research to financial services. This specialization is intended for anyone with a basic knowledge of sequential programming in Java, who is motivated to learn how to write parallel, concurrent and distributed programs. Through a collection of three courses (which may be taken in any order or separately), you will learn foundational topics in Parallelism, Concurrency, and Distribution. These courses will prepare you for multithreaded and distributed programming for a wide range of computer platforms, from mobile devices to cloud computing servers.
To see an overview video for this Specialization, click here! For an interview with two early-career software engineers on the relevance of parallel computing to their jobs, click here.
Acknowledgments
The instructor, Prof. Vivek Sarkar, would like to thank Dr. Max Grossman for his contributions to the mini-projects and other course material, Dr. Zoran Budimlic for his contributions to the quizzes, Dr. Max Grossman and Dr. Shams Imam for their contributions to the pedagogic PCDP library used in some of the mini-projects, and all members of the Rice Online team who contributed to the development of the course content (including Martin Calvi, Annette Howe, Seth Tyger, and Chong Zhou).
Parallel, Concurrent, and Distributed Programming in Java Specialization
Boost Your Programming Expertise with Parallelism. Learn the fundamentals of parallel, concurrent, and distributed programming.
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About this Specialization
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Skills you will gain
Distributed ComputingOptimistic Concurrency ControlParallel ComputingJava Concurrency
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 3 Courses in this Specialization
Course1
Parallel Programming in Java
4.6
596 ratings
This course teaches learners (industry professionals and students) the fundamental concepts of parallel programming in the context of Java 8. Parallel programming enables developers to use multicore computers to make their applications run faster by using multiple processors at the same time. By the end of this course, you will learn how to use popular parallel Java frameworks (such as ForkJoin, Stream, and Phaser) to write parallel programs for a wide range of multicore platforms including servers, desktops, or mobile devices, while also learning about their theoretical foundations including computation graphs, ideal parallelism, parallel speedup, Amdahl's Law, data races, and determinism.
Why take this course?
• All computers are multicore computers, so it is important for you to learn how to extend your knowledge of sequential Java programming to multicore parallelism.
• Java 7 and Java 8 have introduced new frameworks for parallelism (ForkJoin, Stream) that have significantly changed the paradigms for parallel programming since the early days of Java.
• Each of the four modules in the course includes an assigned mini-project that will provide you with the necessary hands-on experience to use the concepts learned in the course on your own, after the course ends.
• During the course, you will have online access to the instructor and the mentors to get individualized answers to your questions posted on forums.
The desired learning outcomes of this course are as follows:
• Theory of parallelism: computation graphs, work, span, ideal parallelism, parallel speedup, Amdahl's Law, data races, and determinism
• Task parallelism using Java’s ForkJoin framework
• Functional parallelism using Java’s Future and Stream frameworks
• Loop-level parallelism with extensions for barriers and iteration grouping (chunking)
• Dataflow parallelism using the Phaser framework and data-driven tasks
Mastery of these concepts will enable you to immediately apply them in the context of multicore Java programs, and will also provide the foundation for mastering other parallel programming systems that you may encounter in the future (e.g., C++11, OpenMP, .Net Task Parallel Library).
Course2
Concurrent Programming in Java
4.5
345 ratings
This course teaches learners (industry professionals and students) the fundamental concepts of concurrent programming in the context of Java 8. Concurrent programming enables developers to efficiently and correctly mediate the use of shared resources in parallel programs. By the end of this course, you will learn how to use basic concurrency constructs in Java such as threads, locks, critical sections, atomic variables, isolation, actors, optimistic concurrency and concurrent collections, as well as their theoretical foundations (e.g., progress guarantees, deadlock, livelock, starvation, linearizability).
Why take this course?
• It is important for you to be aware of the theoretical foundations of concurrency to avoid common but subtle programming errors.
• Java 8 has modernized many of the concurrency constructs since the early days of threads and locks.
• During the course, you will have online access to the instructor and mentors to get individualized answers to your questions posted on the forums.
• Each of the four modules in the course includes an assigned mini-project that will provide you with the necessary hands-on experience to use the concepts learned in the course on your own, after the course ends.
The desired learning outcomes of this course are as follows:
• Concurrency theory: progress guarantees, deadlock, livelock, starvation, linearizability
• Use of threads and structured/unstructured locks in Java
• Atomic variables and isolation
• Optimistic concurrency and concurrent collections in Java (e.g., concurrent queues, concurrent hashmaps)
• Actor model in Java
Mastery of these concepts will enable you to immediately apply them in the context of concurrent Java programs, and will also help you master other concurrent programming system that you may encounter in the future (e.g., POSIX threads, .NET threads).
Course3
Distributed Programming in Java
4.5
212 ratings
This course teaches learners (industry professionals and students) the fundamental concepts of Distributed Programming in the context of Java 8. Distributed programming enables developers to use multiple nodes in a data center to increase throughput and/or reduce latency of selected applications. By the end of this course, you will learn how to use popular distributed programming frameworks for Java programs, including Hadoop, Spark, Sockets, Remote Method Invocation (RMI), Multicast Sockets, Kafka, Message Passing Interface (MPI), as well as different approaches to combine distribution with multithreading.
Why take this course?
• All data center servers are organized as collections of distributed servers, and it is important for you to also learn how to use multiple servers for increased bandwidth and reduced latency.
• In addition to learning specific frameworks for distributed programming, this course will teach you how to integrate multicore and distributed parallelism in a unified approach.
• Each of the four modules in the course includes an assigned mini-project that will provide you with the necessary hands-on experience to use the concepts learned in the course on your own, after the course ends.
• During the course, you will have online access to the instructor and the mentors to get individualized answers to your questions posted on forums.
The desired learning outcomes of this course are as follows:
• Distributed map-reduce programming in Java using the Hadoop and Spark frameworks
• Client-server programming using Java's Socket and Remote Method Invocation (RMI) interfaces
• Message-passing programming in Java using the Message Passing Interface (MPI)
• Approaches to combine distribution with multithreading, including processes and threads, distributed actors, and reactive programming
Mastery of these concepts will enable you to immediately apply them in the context of distributed Java programs, and will also provide the foundation for mastering other distributed programming frameworks that you may encounter in the future (e.g., in Scala or C++).
Instructor
Vivek Sarkar
ProfessorDepartment of Computer Science
About Rice University
Rice University is consistently ranked among the top 20 universities in the U.S. and the top 100 in the world. Rice has highly respected schools of Architecture, Business, Continuing Studies, Engineering, Humanities, Music, Natural Sciences and Social Sciences and is home to the Baker Institute for Public Policy.
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.
How long does it take to complete the Specialization?
There are 3 courses in this Specialization. Based on a weekly commitment of 4-8 hours, you should be able to complete the Specialization in 12 weeks.
What background knowledge is necessary?
The Specialization is targeted at an audience that is already familiar with sequential programming in Java, including a basic knowledge of Java 8 lambdas.
Do I need to take the courses in a specific order?
No, you can take the courses in this Specialization in any order.
Will I earn university credit for completing the Specialization?
You will not earn university credit for completing the Specialization.
What will I be able to do upon completing the Specialization?
This course teaches industry professionals and students the fundamental concepts of parallel programming in the context of Java 8. Parallel programming enables developers to use multicore computers to make their applications run faster by using multiple processors at the same time. By the end of this course, you will learn how to use popular parallel Java frameworks such as ForkJoin and Stream to write parallel programs for a wide range of multicore platforms whether for servers, desktops, or mobile devices, while also learning about their theoretical foundations (e.g., deadlock freedom, data race freedom, determinism).
More questions? Visit the Learner Help Center.
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