4.4
1,466 ratings
229 reviews

#### 100% online

Start instantly and learn at your own schedule.

#### Approx. 16 hours to complete

Suggested: 6 hours/week...

#### English

Subtitles: English

### Skills you will gain

Data StructureParallel ComputingData ParallelismParallel Algorithm

#### 100% online

Start instantly and learn at your own schedule.

#### Approx. 16 hours to complete

Suggested: 6 hours/week...

#### English

Subtitles: English

### Syllabus - What you will learn from this course

Week
1
12 hours to complete

## Parallel Programming

We motivate parallel programming and introduce the basic constructs for building parallel programs on JVM and Scala. Examples such as array norm and Monte Carlo computations illustrate these concepts. We show how to estimate work and depth of parallel programs as well as how to benchmark the implementations....
9 videos (Total 106 min), 5 readings, 3 quizzes
9 videos
Introduction to Parallel Computing15m
Parallelism on the JVM I13m
Parallelism on the JVM II8m
Running Computations in Parallel13m
Monte Carlo Method to Estimate Pi4m
How Fast are Parallel Programs?24m
Benchmarking Parallel Programs17m
Tools Setup10m
Eclipse Tutorial10m
IntelliJ IDEA Tutorial10m
Sbt Tutorial10m
Submitting Solutions10m
Week
2
8 hours to complete

We continue with examples of parallel algorithms by presenting a parallel merge sort. We then explain how operations such as map, reduce, and scan can be computed in parallel. We present associativity as the key condition enabling parallel implementation of reduce and scan....
6 videos (Total 100 min), 2 quizzes
6 videos
Data Operations and Parallel Mapping18m
Parallel Fold (Reduce) Operation18m
Associativity I14m
Associativity II17m
Parallel Scan (Prefix Sum) Operation24m
Week
3
7 hours to complete

## Data-Parallelism

We show how data parallel operations enable the development of elegant data-parallel code in Scala. We give an overview of the parallel collections hierarchy, including the traits of splitters and combiners that complement iterators and builders from the sequential case....
5 videos (Total 51 min), 2 quizzes
5 videos
Data-Parallel Operations I6m
Data-Parallel Operations II8m
Scala Parallel Collections15m
Splitters and Combiners7m
Week
4
7 hours to complete

## Data Structures for Parallel Computing

We give a glimpse of the internals of data structures for parallel computing, which helps us understand what is happening under the hood of parallel collections....
5 videos (Total 57 min), 2 quizzes
5 videos
Parallel Two-phase Construction14m
Conc-tree Data Structure14m
Amortized, Constant-time Append Operation11m
Conc-Tree Combiners4m
4.4
229 Reviews

## 23%

started a new career after completing these courses

## 21%

got a tangible career benefit from this course

### Top Reviews

By ALApr 24th 2018

The course is fairly advanced and you would need to review the materials many times to understand the concept. The assignments are definitely fun and not as straightforward as other courses.

By RCAug 25th 2017

Superb study material. Learnt a lot during this course. I am not much into mathematical stuff, but got a hang of how to break problems and improve efficiency through parallelism.

## Instructors

### Prof. Viktor Kuncak

Associate Professor
School of Computer and Communication Sciences

### Dr. Aleksandar Prokopec

Principal Researcher
Oracle Labs

## About the Functional Programming in Scala Specialization

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....