Spark running on EC2 vs EMR
EMR provides a simple to use Hadoop/spark as service. You just have to select the components you want to be installed (spark, hadoop), their versions, how many machines you want to use and a couple other options and then it installs everything for you. Since you are students I assume you don't have experience in automation tools like Ansible, Puppet or Chef and probably you never had to maintain your own hadoop cluster. If that is the case I would definitively suggest EMR. As an experienced hadoop/spark user, at the same time I can tell you that it has its own limitations. When I used it 6 months ago I wanted to use the latest version of EMR (4.0 If remember correctly) because it supported the latest version of Spark and I had few headaches to customise it to install Java 8 instead of the provided Java 7. I believe it was their early days of supporting Java 8 and they should have fixed that by now. But this is what you miss with all the "all included" solutions, flexibility especially if you are an expert user.
We are students that are working on a graduation project related to the Data Science, we are developing a Recommender Engine using Spark with python (Pyspark) with Android Application (Interface for the users) and we have a faced a lot of roadblocks, one of them was how to keep the Spark script up and running on a cloud for a fast processing and real-time results.
All we knew about EMR that it's newer than EC2 and already has the Hadoop installed on it.
We still have hard time taking the decision on which to use and what are the differences between them dealing with Spark.