Updated course and building descriptions

2 files changed, 2 insertions, 2 deletions

diff --git a/js/campus-coords.js b/js/campus-coords.js
index 580a77c..97eccad 100644
--- a/js/campus-coords.js
+++ b/js/campus-coords.js
@@ -101,7 +101,7 @@ define(function() {
             ]
         }, {
             "name" : "GEWIS",
-            "description": "",
+            "description": "GEWIS is the student association for Data Science and Wiskunde & Informatica (Mathematics & Informatics). Besides your hard studying, you should also relax sometimes. This relaxation could be done at GEWIS. Every thursday afternoon you can take a drink with your fellow students. But GEWIS also provides trips and some leisure activities. You can also learn to organize, since there are lots of different committees you can do.",
             "coords": [
             ]
         }
diff --git a/js/courses.js b/js/courses.js
index 6d04a4a..c973eae 100644
--- a/js/courses.js
+++ b/js/courses.js
@@ -61,7 +61,7 @@ define(['assert'], function(assert) {
         "2IIC0": "Process-aware information systems are information systems that are configured on the basis of process models. In some systems the process models are explicit and can be adapted while in other systems they are implicit. It is clear that in any enterprise, business processes and information systems are strongly intertwined. In this course, we study the fundamental relationship between systems and processes and we model complex systems involving processes, humans, and organizations.",
         "2IID0": "In Web Analytics course we focus on the utility of different technologies for understanding the Web as a whole, for modeling the behavior of the individual Web users and user groups, for using Web as an experimentation platform. We will cover the topics of OLAP style data exploration, data mining, and social network analysis. We will give a special attention to understanding search, recommendations and advertisements on the Web.",
         "2IO90": "How can we automatically put labels (like city names) on a map in such that the labels do not overlap? How can we compute train schedules that optimally use the available tracks and trains? How can we reconstruct 3D objects from laser scans? These are just a few examples of challenging problems that require efficient algorithmic solutions and effective software implementations of those solutions. In this course you will attack such an algorithmic problem in a team of five or six students.",
-        "DS004": "",
+        "DS004": "In the end of your bachelor you have to do a final project. The choices in the project are mostly up to you. You choose whether to work on your own or in pairs. You choose what area in data science you cover in your project. And you choose the kind of project."
 
     };