Add reviews for CSSE1001 and STAT2203

tex/courses/subjects/CSSE1001.tex

@@ -2,16 +2,26 @@
 \courseTemplate[
 code = {CSSE1001},
 title = {Introduction to Software Engineering},
-score = {4},
+score = 3,
 prereq = {None},
 contact = {2L, 2P, 1T},
 coordinator = {Dr Peter O\'Shea ([email protected])},
 assessment = {
-example & example\% & example \\
+MyPyTutor Exercises & 10\% & Online exercises which can be completed any time \\
+Assignment 1 & 5\% & Python assignment \\
+Assignment 2 & 10\% & Python assignment \\
+Assignment 3 & 25\% & Python assignment \\
+Final Exam & 50\% & Multiple choice exam; often re-uses questions from past years \\
 },
 review = {
-    review here
+    This course is UQ's introductory programming course; it does not assume any prior programming experience and is often taken by students outside of ITEE, as well as being compulsory for most ITEE degrees.\\
+
+    The course teaches students Python 3 programming, covering imperative programming, introducing object orientation, as well as GUI programming with the TKinter library. After each assignment, students are `interviewed' by a tutor, with marking occurring at that time. Your ability to explain your assignment forms a component of your mark.\\
+
+    The final exam is entirely multiple choice, and questions are often taken directly from past years, so studying past papers is highly advised. Time is usually not a huge pressure in the final exam, as many multiple choice questions can be answered very quickly.\\
+
+    For students with prior programming experience (hobbyist or formal), the course's content will likely be retreading familiar topics and will overall be quite easy. The course will require more effort for those with no programming experience, but a high grade is still quite achievable.\\
 },
 preparation = {
-    \item thingo
+    \item Install Python 3 and perhaps run through a tutorial online
 }]{}

tex/courses/subjects/DECO2500.tex

@@ -21,7 +21,6 @@
     The final exam will quiz you on the textbook. Make sure to read it cover to cover, as you will be quizzed on specific case studies in the book. Past exam questions will be your friend when studying for the final exam. \\
 
     Penelope Sanderson is a lecturer from the Psychology department. If you approach the course as more of a psychology course than an engineering course, then you will have better expectation and understanding of the activities. Not everyone will enjoy this course, but the course gives a solid foundation to understanding how usabilitiy testing makes for better software.
-
 },
 preparation = {
     \item Prepare for the weeky practical classes beforehand. The criteria sheets for each week are released before the class begins, so no excuses.

tex/courses/subjects/STAT2203.tex

@@ -2,16 +2,27 @@
 \courseTemplate[
 code = {STAT2203},
 title = {Probability Models and Data Analysis for Engineering},
-score = {4},
+score = {3},
 prereq = {MATH1051},
 contact = {3L, 1T, 1P},
 coordinator = {Dr Thomas Taimre ([email protected])},
 assessment = {
-example & example\% & example \\
+Assignment Problems & 48\% & 6 problem-based assignments \\
+Mid-sem exam & 13\% & Problem-based exam \\
+Final exam & 39\% & Problem-based exam \\
 },
 review = {
-    review here
+    This course teaches the basics of statistics and statistical analysis. Its content is very heavy on the maths and less so on practical application, which may be a positive or negative depending on the student. \\
+
+    Throughout the course, you will learn about basic probability theory, probability distributions and hypothesis testing. The assignments usually have some questions which are answered by hand, and others that require coding (the course primarily uses MATLAB; in some years it has allowed students to use whichever language suits them) to develop and run statistical simulations.\\
+	The problems on the final examination have in the past been similar to the assignments, but often of higher difficulty, requiring synthesis of multiple concepts.\\
+
+	Overall, the course content is very useful, as a working knowledge of basic statistics is required for many higher level courses (for example, AI and Machine Learning). However, students may find the content of this course quite `dry', and the assessment difficult.
 },
 preparation = {
-    \item thingo
+    \item Read up on basic probability and statistics
+
+    \item Begin the assignments early; problems often take several days to fully `get'
+
+    \item The lectures are fully recorded with complete slides uploaded, and are vital for revision material
 }]{}