About this Course
4.7
1,666 ratings
351 reviews
Specialization
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100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Hours to complete

Approx. 15 hours to complete

Suggested: 6 hours/week...
Available languages

English

Subtitles: English...

Skills you will gain

Scala ProgrammingBig DataApache SparkSQL
Specialization
100% online

100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Hours to complete

Approx. 15 hours to complete

Suggested: 6 hours/week...
Available languages

English

Subtitles: English...

Syllabus - What you will learn from this course

Week
1
Hours to complete
12 hours to complete

Getting Started + Spark Basics

Get up and running with Scala on your computer. Complete an example assignment to familiarize yourself with our unique way of submitting assignments. In this week, we'll bridge the gap between data parallelism in the shared memory scenario (learned in the Parallel Programming course, prerequisite) and the distributed scenario. We'll look at important concerns that arise in distributed systems, like latency and failure. We'll go on to cover the basics of Spark, a functionally-oriented framework for big data processing in Scala. We'll end the first week by exercising what we learned about Spark by immediately getting our hands dirty analyzing a real-world data set....
Reading
7 videos (Total 105 min), 5 readings, 3 quizzes
Video7 videos
Data-Parallel to Distributed Data-Parallel10m
Latency24m
RDDs, Spark's Distributed Collection9m
RDDs: Transformation and Actions16m
Evaluation in Spark: Unlike Scala Collections!20m
Cluster Topology Matters!8m
Reading5 readings
Tools setup10m
Eclipse tutorial10m
Intellij IDEA Tutorial10m
Sbt tutorial10m
Submitting solutions10m
Week
2
Hours to complete
7 hours to complete

Reduction Operations & Distributed Key-Value Pairs

This week, we'll look at a special kind of RDD called pair RDDs. With this specialized kind of RDD in hand, we'll cover essential operations on large data sets, such as reductions and joins....
Reading
4 videos (Total 59 min), 2 quizzes
Video4 videos
Pair RDDs6m
Transformations and Actions on Pair RDDs20m
Joins17m
Week
3
Hours to complete
1 hour to complete

Partitioning and Shuffling

This week we'll look at some of the performance implications of using operations like joins. Is it possible to get the same result without having to pay for the overhead of moving data over the network? We'll answer this question by delving into how we can partition our data to achieve better data locality, in turn optimizing some of our Spark jobs....
Reading
4 videos (Total 57 min)
Video4 videos
Partitioning14m
Optimizing with Partitioners11m
Wide vs Narrow Dependencies16m
Week
4
Hours to complete
8 hours to complete

Structured data: SQL, Dataframes, and Datasets

With our newfound understanding of the cost of data movement in a Spark job, and some experience optimizing jobs for data locality last week, this week we'll focus on how we can more easily achieve similar optimizations. Can structured data help us? We'll look at Spark SQL and its powerful optimizer which uses structure to apply impressive optimizations. We'll move on to cover DataFrames and Datasets, which give us a way to mix RDDs with the powerful automatic optimizations behind Spark SQL....
Reading
5 videos (Total 133 min), 2 quizzes
Video5 videos
Spark SQL17m
DataFrames (1)26m
DataFrames (2)30m
Datasets43m
4.7
Career direction

10%

started a new career after completing these courses
Career Benefit

83%

got a tangible career benefit from this course
Career promotion

12%

got a pay increase or promotion

Top Reviews

By CCJun 8th 2017

The sessions where clearly explained and focused. Some of the exercises contained slightly confusing hints and information, but I'm sure those mistakes will be ironed out in future iterations. Thanks!

By CRApr 10th 2017

Great introduction to spark. Fun assignments. Since it was the first ever session, there were quite a few kinks with the assignments. But the discussion forums rescued me any time I was stuck.

Instructor

Avatar

Dr. Heather Miller

Research Scientist
EPFL

About École Polytechnique Fédérale de Lausanne

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....
Functional Programming in Scala

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.