Certificate in Data Analytics
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Course Overview
The Certificate in Data Analytics is a 1-year part-time conversion programme in Applied Data Analytics which was devised in response to the highlighted need for data savvy graduates. It will provide learners with skills in the areas of statistics, programming and databases that will enable them to transfer much of the domain specific knowledge/skill already gain in their primary degree(s) to the IT and Data Analytics sector.
Data Analytics is a contributor to key technologies in many areas of Business, Engineering and Computing. This programme is a first step into the area of Data Analytics, providing upskilling and reskilling opportunities. This 1-year part-time programme, consists of a technical subset of the modules being offered in year 1 of the Higher Diploma in Data Analytics. It aims to provide participants with a strong foundation in statistical techniques, spreadsheet technologies and statistical programming using R.
This course is aimed at:
- Candidates with strong numeracy skills and a basic knowledge of statistics who wish to become more data savvy. No prior programming exposure is required.
- Graduates with strong numerate skills who wish to pursue a career in the expanding area of Data Analytics.
- Professionals who wish to develop their Data Analytics skills to apply them to real problems in their current work domains.
Career Opportunities
The course provides a starting point for a career in areas such as:
- Data Analyst
- Data Scientist
- Data Engineer
- Progression routes open to graduates of the Certificate in Data Analytics, may include conversion to the Higher Diploma in Data Analytics or progression to the PGDip / Masters in Science in Data Analytics (subject to meeting additional entry requirements).
Course Delivery and Modules
This course is delivered using a blended learning approach with weekly interactive and hands-on practical lab-based sessions supported by independent and online learning.
This course will run over 2 semesters, with online synchronous classes delivered on two evenings per week, typically Monday and Wednesday between 6pm and 9pm, potentially with some asynchronous content (videos/practical tasks) to be completed within the same week, but at a time of the students choosing.
Weekly classes will be interactive, with hands-on practical lab-based sessions supported by independent and online learning. Attendance and participation in live classes will be important in order to master the material.
Participants will be required to attend onsite for any formal end-of-semester examinations, these will occur during examination periods in Jan/ May, but students will be advised of dates well in advance. This course contains just one such examination, Statistics Using R, which is a year-long module.
- Statistics using R - (Semester 1 of 2)
- Spreadsheet Data Analytics
- Applied Database Systems
- Statistics using R - (Semester 2 of 2)
Fees and Funding
This is a PEACEPLUS-funded programme, delivered via the SECBA project. More details on fees to follow.
Entry requirements
- ANY Honours (Level 8) Degree with 15 credits of Mathematics and/or Statistics
- OR Level 7 Degree with 15 credits of Mathematics and/or Statistics
- AND at least 2 years of work experience together with strong numeracy skills.
No prior programming exposure is required.
Recognition of Prior Learning
Applicants who do not meet the standard academic entry requirements but have significant relevant experience (certified and/or experiential) may apply to access this programme via the Recognition of Prior Learning (RPL) route. Learn more about RPL at DkIT
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Disclaimer: All module titles are subject to change and for indicative purposes only. All courses are delivered subject to demand and timetables are subject to change. Elective Module options will only run subject to student numbers. The relevant Department will determine the viability of each elective module option proceeding depending on the number of students who choose that option. Students will be offered alternative elective modules on their programme should their preferred elective option not be proceeding. Award Options for Common Entry Programmes: The relevant Department will determine the viability of each award option proceeding depending on the number of students who choose either option. If the numbers for one of the Award options exceed available places, students for this option will be selected based on Academic Merit (highest grades).