@@ -6,6 +6,10 @@ by: Julien Richard-Foy
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includeTOC : false
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---
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+ > ** Update** : After a couple of years experimenting with Open edX, we decided
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+ > to shut down these course instances. You can find an up-to-date list of
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+ > online courses [ here] ( https://docs.scala-lang.org/online-courses.html ) .
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We are thrilled to announce that our 4 main MOOCs are now also available
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on an [ Open edX instance managed at EPFL] ( https://courseware.epfl.ch ) .
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@@ -18,16 +22,16 @@ that confirm that you successfully completed a course).
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As a reminder, the courses are the following:
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- - [ Functional Programming Principles in Scala] ( https://courseware.epfl.ch/courses/course-v1:EPFL+progfun1+2018_T1/info ) :
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+ - Functional Programming Principles in Scala:
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An introduction to functional programming (pure functions, recursion, pattern matching, higher-order
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functions, immutable data types, type parameters, equational reasoning),
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- - [ Functional Program Design in Scala] ( https://courseware.epfl.ch/courses/course-v1:EPFL+progfun2+2018_T1/info ) :
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+ - Functional Program Design in Scala:
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A follow-up of the first course, showing how to apply the functional programming style
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to larger programs. Covers topics such as monads, lazy evaluation, property-based testing,
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futures and dataflow programming.
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- - [ Parallel Programming] ( https://courseware.epfl.ch/courses/course-v1:EPFL+parprog1+2018_T1/info ) :
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+ - Parallel Programming:
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Introduces the fundamentals of parallel programming, from task parallelism to data parallelism,
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- - [ Big Data Analysis with Scala and Spark] ( https://courseware.epfl.ch/courses/course-v1:EPFL+scala-spark-big-data+2018-T1/info ) :
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+ - Big Data Analysis with Scala and Spark:
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Extends the data parallel paradigm to the distributed case (as opposed to shared-memory parallel
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or sequential collections), using Spark.
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