MSc Computer Science (Negotiated Learning)

big tasty

Hi everyone,



I’m starting the MSc in Computer Science (Negotiated Learning) in Sept. and I just wanted to send a message out to see if anyone here will be joining me? I’ve looked through past threads here on boards, but I haven’t really seen much feedback on the course itself. Has anyone taken the course already? If so, what did you make of it? From I hear the workload can be pretty full on at times, but a part from that I don’t really know what to expect.

Also, I’m interested to see what modules people are thinking of choosing. I was initially interested in the Data Science stream, but I think I’m going to just dip in and out of the different modules instead. My plan is to take:

Semester I
Professional Java Programming Part I (COMP41600)
Professional Java Programming Part II (COMP41620)
Web Services in Cloud Computing (COMP41530)
Virtualisation & Cloud Computing (COMP41500)

Semester II
Introduction to Relational Databases and SQL Programming (COMP40725)
Data Science in Python (COMP41680)
Contemporary Software Development (COMP47480)
Java Technologies (COMP41490)
Big Data Programming (COMP47470)


I’m hoping we can sit in on in other classes too. I’m interested in some of the classes below, although I wonder how practical they would be for life outside of the classroom…

Distributed Computing (COMP30220)
Performance of Computer Systems (COMP40010)
Topics in Computational Network Analysis and Modelling (COMP47260)
Big Data Programming (COMP47470)
Numerical Algorithms (ACM40290)

So a part from brushing up on Java/Python/SQL, I’m wondering what do people think is the best way to prepare for a course like this? 


A part from that, if anyone cares to share their thoughts it would be much appreciated!


OneOfThem Stumbled

big tasty wrote: »

Hi everyone,
I’ve looked through past threads here on boards, but I haven’t really seen much feedback on the course itself. Has anyone taken the course already? If so, what did you make of it?

I've never heard of anyone from Ireland doing the course before, so that would probably be the reason.

big tasty wrote: »

I’m hoping we can sit in on in other classes too.


Only research students in UCD can audit modules (officially sit in), but unofficially you probably can (depending on the lecturer, naturally). There are only a couple of modules where space is likely to be a real factor. You might want to ask the undergraduate students to allow you onto their facebook group (stage 4 students), as the material shared there would likely be helpful. Plus you'll be in some of their modules anyway.

big tasty

OneOfThem Stumbled wrote: »

I've never heard of anyone from Ireland doing the course before, so that would probably be the reason.

That's unusual. Why do you think that is? I imagined that most people taking the course would be Irish

OneOfThem Stumbled

big tasty wrote: »

That's unusual. Why do you think that is?

Non-EU fees. Could be different this year though.

awhir

Hey,

I'm starting this course too in September so I will be joining you . I'm siding more on the data science side of things, Currently I am looking at these streams but would love to get some feedback from someone who has already taken them.

Machine Learning Blended Delivery (COMP47460)

Advanced Machine Learning (COMP47590)

Text Analytics (COMP47600)

Data Mining (COMP40370)

Topics in Computational Network Analysis and Modelling (COMP47260) (See COMP47270 under ASE modules below for timetable information)

Data Science Methods in Python (COMP41680)

Introduction to Data Analytics (STAT40720) (Approval reqd)

Data Programming (Introduction to R) (STAT40620) (Approval reqd)

Information Visualisation (COMP40610)

Big Data Programming (COMP47470)

~Decision Analytics (MIS30010)

~Introduction to Information Security (COMP41280)

rainbow kirby

OneOfThem Stumbled wrote: »

I've never heard of anyone from Ireland doing the course before, so that would probably be the reason.

*waves*

I'm Irish and did it in the first year that the course ran in its current format (2009/10). We didn't have a data science stream back then so about 5 of us basically made up our own from the ruins of the old Computational Science masters and a few other maths/stats courses.