diff --git a/episodes/02-submit-job.Rmd b/episodes/02-submit-job.Rmd
index a9c3a63..208b376 100644
--- a/episodes/02-submit-job.Rmd
+++ b/episodes/02-submit-job.Rmd
@@ -166,7 +166,7 @@ time mpirun --map-by ppr:4:node Rscript hello_balance.R
 ::::::::::::::::::::::::::::::::::::: keypoints 
 
 - Parallel R code distributes work
-- There is shared memory and distributed memory parallelizm
+- There is shared memory and distributed memory parallelism
 - You can test parallel code on your own local machine
 - There are several different job schedulers, but they share many similarities so you can learn a new one when needed
 
diff --git a/episodes/03-multicore.Rmd b/episodes/03-multicore.Rmd
index 4dd2792..f2bb82f 100644
--- a/episodes/03-multicore.Rmd
+++ b/episodes/03-multicore.Rmd
@@ -6,7 +6,7 @@ exercises: 2
 
 :::::::::::::::::::::::::::::::::::::: questions 
 
-- Can parallelization decrease time to solution for my program?
+- Can parallelisation decrease time to solution for my program?
 - What is machine learning?
 
 ::::::::::::::::::::::::::::::::::::::::::::::::
@@ -146,7 +146,7 @@ time Rscript rf_mc.r --args 128
 ::::::::::::::::::::::::::::::::::::: keypoints 
 
 - To evaluate the fitted model, the availabe data is split into training and testing sets
-- Parallelization decreases the training time
+- Parallelisation decreases the training time
 
 ::::::::::::::::::::::::::::::::::::::::::::::::
 
diff --git a/episodes/04-blas.Rmd b/episodes/04-blas.Rmd
index e35400a..881aa34 100644
--- a/episodes/04-blas.Rmd
+++ b/episodes/04-blas.Rmd
@@ -14,7 +14,7 @@ exercises: 2
 
 - Introduce the Basic Linear Algebra Subroutines (BLAS)
 - Show that BLAS routines are used from R for statistical calculations
-- Demonstrate that parallelization can improve time to solution
+- Demonstrate that parallelisation can improve time to solution
 
 ::::::::::::::::::::::::::::::::::::::::::::::::
 
diff --git a/episodes/05-mpi.Rmd b/episodes/05-mpi.Rmd
index f2784ac..2bf8884 100644
--- a/episodes/05-mpi.Rmd
+++ b/episodes/05-mpi.Rmd
@@ -1,5 +1,5 @@
 ---
-title: "MPI - Distributed Memory Parallelizm"
+title: "MPI - Distributed Memory Parallelism"
 teaching: 10
 exercises: 0
 ---
@@ -13,7 +13,7 @@ exercises: 0
 ::::::::::::::::::::::::::::::::::::: objectives
 
 - Demonstrate how to submit a job on multiple nodes
-- Demonstrate that a program with distributed memory parallelizm can be run on a shared memory node
+- Demonstrate that a program with distributed memory parallelism can be run on a shared memory node
 
 ::::::::::::::::::::::::::::::::::::::::::::::::
 
diff --git a/episodes/06-pbdmpi.Rmd b/episodes/06-pbdmpi.Rmd
index bcec314..8f79989 100644
--- a/episodes/06-pbdmpi.Rmd
+++ b/episodes/06-pbdmpi.Rmd
@@ -408,7 +408,7 @@ finalize()
 ::::::::::::::::::::::::::::::::::::: keypoints 
 
 - The message passing interface offers many operations that can be used to
-  efficiently and portably add parallelizm to your program
+  efficiently and portably add parallelism to your program
 - It is possible to use parallel libraries to minimize the amount of parallel
   programming you need to do for your data exploration and data analysis
 
diff --git a/episodes/07-random-forest-mpi.Rmd b/episodes/07-random-forest-mpi.Rmd
index a3c7823..8f765e4 100644
--- a/episodes/07-random-forest-mpi.Rmd
+++ b/episodes/07-random-forest-mpi.Rmd
@@ -1,5 +1,5 @@
 ---
-title: "MPI - Distributed Memory Parallelizm"
+title: "MPI - Distributed Memory Parallelism"
 teaching: 10
 exercises: 2
 ---
@@ -12,8 +12,8 @@ exercises: 2
 
 ::::::::::::::::::::::::::::::::::::: objectives
 
-- Demonstrate that distributed memory parallelizm is useful for working with large data
-- Demonstrate that distributed memory parallelizm can lead to improved time to solution
+- Demonstrate that distributed memory parallelism is useful for working with large data
+- Demonstrate that distributed memory parallelism can lead to improved time to solution
 
 ::::::::::::::::::::::::::::::::::::::::::::::::
 
@@ -146,7 +146,7 @@ time mpirun --map-by ppr:32:node Rscript rf_mpi.R
 ::::::::::::::::::::::::::::::::::::: keypoints 
 
 - Classification can be used for data other than digits, such as diamonds
-- Distributed memory parallelizm can speed up training
+- Distributed memory parallelism can speed up training
 
 ::::::::::::::::::::::::::::::::::::::::::::::::