Diploma in Machine Learning Course Overview and Audience
According to Gartner’s Hype Cycle 2019, over the next decade, data analytics and AI will augment workers’ efficiency, as companies rely on leading tech to beat out competitors. The Machine Learning modules on this course will equip the learner with the skills necessary to tackle a wide range of unsupervised learning problems, such as cluster analysis and text analytics. Both techniques are widely used in the analysis of business data as they allow the enterprise to develop a deeper understanding of their customers. These modules build on and draw from the Introduction to Programming for Data Analytics module to equip the learner with practical experience of the use of commonplace classification and regression approaches. The Digital Transversal skills module will empower the learner using both collaborative tools and techniques and individual insights into problem solving in a digital domain with a focus on the workplace.
This modular course will appeal to a range of adult learners who may or may not be currently in employment and wish to up-skill, or returners and other groups who may wish to re-skill and are seeking to develop their knowledge in machine learning applications on a flexible modular basis. It will give those working in IT, marketing, finance and other industries a knowledge of machine learning which will help enable them to better manage their data for improved business forecasting and decision making.
- Digital Transversal Skills
- Introduction to Programming for Data Analytics
- Machine Learning I
- Machine Learning II
Those who are in employment/working :
For eligible applicants who are currently in employment/working 90% of the tuition fees will be covered by the HEA and the remaining 10% is payable by the student or their employer.
- The Course Tuition Fee is €2,400 so €240 euro is payable by the student or their employer
Those who are unemployed, formerly self-employed and ‘Returners’:
The course is free and 100% funded for eligible applicants who are unemployed, formerly self-employed or who are classified by the HEA as ‘Returners’ or ‘Homemakers’.
Admission to this modular programme is through one of the following:
Evidence of prior learning, including experiential learning,
Possession of an NFQ level 5 award, including leaving certificate, FET award, or equivalent.
In addition, all applicants must evidence competence in mathematics equivalent to O6 standard in leaving certificate and competence in the use of IT. Basic computer literacy is not sufficient for this programme.
International applicants whose first language isn’t English must demonstrate a minimum competency in the English Language of CEFR B2+.
Applicants are encouraged to apply for entry based on prior learning (RPL) or prior experiential learning (RPEL) in line with the College policy. The College will thoroughly assess applications received through RPL and RPEL to ensure that candidates are able to evidence learning to an appropriate standard – normally the framework level equivalent to the direct entry qualification requirement and demonstrate potential to succeed and benefit from the programme.
This course will be delivered online. Online activities can include live or pre-recorded lectures, independent learning and assessment activities such as research tasks, discussion forums, simulations, quizzes and e-portfolio work along with online group activities such as live classes, group project work, virtual labs and tutorials.