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Frequently Asked Questions
How long does the programme take to complete?
The MSc programmes require a two-year part-time commitment. The MSc in Electronic and Computer Technology Qualifier (MQTY) is a one year programme; successful completion of this Qualifier programme allows transfer, with full credit, to the MSc in Electronic and Computer Technology (IoT Major) (MCTY) programme, which will take one more year to complete.
What level on the NFQ are the programmes?
If I successfully complete the MSc in Electronic and Computer Technology Qualifier (MQTY), can I go on to complete the Master’s programme?
Yes, you can. This will take one more year of study to complete the full MSc programme.
I have a Master’s Degree already; can I still take a DCU Skillnet MSc programme?
Yes, you can. The aim of the Skillnet programmes are to upskill or reskill people in employment to fill anticipated skills shortages in key areas. So, if you have a Masters or PhD already, you can still register for one of these programmes.
What are the academic entry requirements?
MSc in Electronic and Computer Technology (IoT Major)
How do I apply?
What happens after I apply?
Your applications (including transcripts) will be assessed in the first instance by Skillnet to make sure that you have submitted all the details requested. A copy of your degree certificate is not sufficient. You must request a copy of all of your transcripts from the institution that awarded your degree or diploma, if you do not have them already. Failure to supply transcripts will delay the processing of your application. The next step is to check that you meet the English language requirements. If English is not your first language, then your academic qualifications will be assessed to make sure you meet the entry requirements for the programme. Once you have passed the initial eligibility screening you will be asked to apply for your programme of interest through the Postgraduate Application Centre (www.pac.ie) using the course code provided. As stated above, even if you meet the minimum entry requirements, you may not be offered a place on the programme, as places are limited and this is a competitive process. You may also be interviewed on the phone by the Programme Chair. If you are offered a place, you must accept this offer through PAC.
Do I have to attend Dublin City University if I wish to study on one of Skillnet funded programmes?
My personal circumstances have changed and I won’t be able to complete the full MSc. What are my options?
There is provision for Graduate Certificate and Graduate Diploma awards, where participants can opt to complete a smaller set of modules and still exit with a formal Level 9 award.
What is the approximate time commitment required in terms of lecture/study time per semester for the MSc programmes?
The approximate time commitment is about 20 hours per week, based on studying two 7.5 credit modules per semester. However, because the programme is delivered online, you have the flexibility to adapt you study schedule to optimally fit with your life and work commitments.
How often do I have to attend campus?
What are the AI and Machine Learning topics covered on this program?
The module EE514 Data Analytics and Machine Learning (7.5 credits out of 90 total). This module will provide students with fundamental and advanced skills required for data analytics, including: data management, processing, summarization, and predictive analytics. It is focused on providing students with a strong theoretical foundation, along with the ability to make practical use of the advanced techniques in the field. The Python programming language will be used for demonstrating the use of various techniques throughout the module, giving students practical tools for solving relatively sophisticated and broadly-defined real world problems in a well-established and widely-used programming environment.
What are the assessment methods?
The 9 taught modules each involve exam and continuous assessment (CA) elements. The typical arrangement is 25% CA and 75% terminal exam, but it is 50%/50% in some modules. The project elements are 100% continuous assessment.
Programme Title |
Mode of Delivery |
|
|
MSc in Electronic and Computer Technology (IoT Major) (MCTY)
[PAC Code DC869] |
Online/ Blending learning |
Campus attendance required for no more than three on-site workshops and for exams. The onsite workshops would entail a half-day induction and 1 to 2 days (maximum) for the project module(s) each year. |
OOP with Embedded Systems Connected Embedded Systems Real Time digital signal processing Data Analysis & Machine Learning Web application development Network Stack Implementation Security for Wireless networks Entrepreneurship for Engineers RD&I training and project planning MSc Project – IoT major |
MSc in Electronic and Computer Technology Qualifier (MQTY) [PAC Code DC870] |
Online |
Campus attendance required for no more than three on-site workshops and for exams. The onsite workshops would entail a half-day induction and 1 to 2 days (maximum) for the project module(s) each year. |
OOP with Embedded Systems Connected Embedded Systems Real Time digital signal processing Data Analysis & Machine Learning Web application development Network Stack Implementation Security for Wireless networks Entrepreneurship for Engineers RD&I training and project planning |