DATA1001: Intro to Data Science and Decisions

3x 15% assessments and a 55% final exam.

No formal prerequisites. But you will actually die if you don't know advanced statistics including things like Baye's Theorem, lots of probability theory, monte carlo methods etc.

Not a very well designed course at all. Firstly, let's sort out the data science part. This course is not real data science, it is basically business intelligence and data analytics. Real data science involves machine learning algorithms and artificial intelligence, which was not at all even mentioned in any aspect of the course. It was more related to SQL, business analytics and statistics etc. The ideal real data science course would have discussed ground-breaking advancements in AI such as deep learning, convolutional neural networks (and other types of neural networks), general AI, etc. Also, the mathematics section of the course had the cohort up in arms. The mathematics lecturer had a PhD in statistics and the content was extremely difficult, and definitely not suitable for this level - I would even argue that it would be at a masters level.

The 3x 15% assessments were pretty easy, I ended up with like 90+ in that, but then the finals were brutal (partially because I didn't put much effort into that, but also because of the statistics part of the course being extremely difficult and unsuitable) - I'd hope they'll improve on this after all the criticism received.
Overall, do not do this course if you don't need to (e.g. as a gen ed or elective). It is not worth it.

A 2 hour lecture every Monday, and 2x one hour labs every week

4/5

Yes

Three different lecturers for the three different parts (Business, Computing and Maths)

Lecture slides will be available on moodle. No other specific material that will help with the content.

1/5

N/A

2017, sem 2

72