Online Programmes in Data Analytics - Studying in an Online Environment
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The Online MSc in Data Analytics covers 18 5-credit modules, 2 per semester over 9 semesters or 3 years. The Profesional diploma covers the first 4 of these modules.
This first year is designed to introduce you to statistical and mathematical concepts in Data Analytics and Data Mining, and to get you started on programming with data. The second year is split between understanding the theory behind statistical and mathematical models for data via predictive analytics, and dealing with data sets at scale using Python and multivariate techniques. The final year covers some advanced methods Monte Carlo, Bayesian analysis, time series data, and complex stochastic models.
Our Date Analytics programmes give you a lot of flexibility.
The Online Professional Diploma (ProfDip) covers the first four modules of the Online MSc which contains 18. Students can register for the ProfDip if they just want a taster of Data Analytics and then transfer on to the MSc afterwards (if they achieve 3.08 or higher GPA in the Professional Diploma modules).
Alternatively, you can register for the full MSc and stop after two modules to gain the Professional Cert., after four modules to gain the Professional Diploma, after six modules to gain a Graduate Certificate, or twelve modules to gain a Graduate Diploma.
To complete the course, you must have access to a relatively modern computer which matches the minimum specifications required to run the UCD software, for more details please click here. The Online MSc and Professional Diploman in Data Analytics are delivered through the UCD Blackboard system and consist of:
Videos and demonstrations by the lecturers
Interactive learning reinforcement quizzes
Screen recordings to demonstrate computer programmes
Online assessed multiple choice quizzes
Interactive discussion boards
Virtual classroom environments
You will be expected to spend around 10 hours per week per module watching videos and performing your own study. We require students to complete homeworks or quizzes every few weeks so that we can monitor their progress. In addition to making the study materials available, lecturers will spend around 2 hours per week answering student queries through the course discussion boards, or through a virtual classroom environment. Tutors will also provide regular additional support through the online portal.
You are not required to attend any lectures at the UCD campus as part of the course. However, you much attend for one or two days at the end of each semester to take exams in the two modules taken that semester. Students must be available to travel to UCD for one or two days during the standard UCD exam period. Exam periods can be found by clicking here. Typically students only need to attend for one day but if you have resit or repeat exams to take you will typically need to attend for two days.
Failure to attend the exam on the specified day will result in you failing the module. Students will be informed of the specified exam dates at the start of each semester.
The Blackboard Virtual Learning Environment (VLE) is used to provide elearning services to staff and students. It allows lecturers to share course materials, post announcements for students, and run quizzes and surveys. Blackboard also includes a Virtual Classroom facility, discussion forums and various other course tools
At present all modules are compulsory and we do not allow substitutions.
Our experience from previous students is that those who are studying online work best when taking no more than 2 modules per semester. Taking one module per semester adds a substantial delay to the completion of the MSc so is not permitted.
The Online MSc in Data Analytics covers 18 5-credit modules, two per semester over 9 semesters or 3 years.
The programme runs in line with the UCD academic calendar.
We are unable to delay a module until the following semester but we structure our online modules (especially the summer ones) flexibly so that students can complete the module at their own pace. This means that, for example, a student could complete a substantial proportion of the module in the early weeks leaving them free for a few weeks to take holidays or other breaks as required. We don’t see it as necessary that every student must complete their study on a per-week basis as we would with traditional offline modules.
If you need to take a longer break from you studies you can apply for a leave of absence.
Once fees are paid in full or part paid by installment and a photo is uploaded to the SIS account, a member of staff will post the Student UCard directly to the address provided in the origianl application.
It is not possible to take exams online.
Students are required to attend for one day at the end of each semester to take exams in the two modules. Students must be available to travel to UCD for one or two days during the standard UCD exam period. Failure to attend exams on the specified day will result in failing the modules. Students will be informed of the specified exam days during each semester.
Subject to demand we will be run an exam centre for the Professional Diploma in Data Analytics in Beijing ?????????? ??-??????? .
We keep close eye on students throughout the semester to ensure that those taking the module do not fall behind without being offered extra help. However, if you do fail a module you can re-sit it in the next semester. If you find that you are running into difficulties please make sure you tell the module co-ordinator immediately so that we can arrange for extra help.
No. A MOOC is a recent phenomenon whereby institutions enter into very large scale free teaching of popular subjects. By contrast our online programmes are personally mentored by academic staff and teaching assistants and we give personalised feedback to each student both through the return of written work, and through discussion boards which we regularly monitor. Furthermore, the exams set at the end of each semester lead to a full UCD qualification at the same standard as any other UCD qualification