This course is eligible for 80% funding through the HCI Micro-Credential Course Learner Subsidy. Please refer to the fees and how to apply sections for specific details and eligibility criteria.
This award in Applied Data Science and Analytics is a constituent of the MSc in Applied Data Science and Analytics, running fully online. Developed with industry for industry, it has gained a significant reputation as a high quality, challenging and very rewording programme with a practical focus.
Focused on the knowledge and skills to select, apply and evaluate data science techniques, the programme emphasises discovering knowledge that can add value to a company. Learners will gain both an in-depth theoretical understanding and practical hands-on experience, including keeping abreast of current research and state of the art in data science related topics. The programme is designed for students in the workplace that need to upskill or reskill in data science and text analytics.
It comprising of two modules that are designed to work together to cover all stages of a data science methodology from defining business objectives, exploration of and understanding your data, assessing data quality and bias, understanding the implications of data preparation choices, tuning and interrogating data models, and critically evaluating results with respect to a business objective. Assessments are adaptable to individual business contexts and interests.
Data Science Algorithms runs one evening a week from September 2024 to December 2024, final assessments to due in early January. Data Exploration and Pre-Processing runs two evenings a week from January to March with assessments completed by early May.
Contact hours are synchronous, online, from 6pm to 9pm, and are also recorded. One-to-one support is also available throughout the week.
Second Class Honours Grade 2 (GPA 2.5 or equivalent), in a NFQ Level 8 Degree in Computing, Science, Engineering, Business with IT, or equivalent qualification. The acceptance of candidates with Third Class Honours degrees and appropriate work experience will be allowed provided there is evidence that the candidate can cope with the learning objectives of the course.
- an ability to evaluate and critically appraise data science techniques with respect to a challenging business objective and structured dataset; and apply a range of data science techniques to address specific problems.
- an understanding and appreciation of the need for quality and integrity and an awareness of ethical concerns arising from data analysis.
- advanced theoretical and practical knowledge and skills relevant to data science including recent developments; and the key stages of relevant development methodologies.
- an ability to reflect on their strengths and weaknesses; recognition of the need to constantly update knowledge and skills; and an attitude based on initiative, responsibility and problem ownership
- interpersonal and communication skills to: discuss current challenges and research; and report on analysis results with respect to a business objective.
Average of 3 contact hours per week and additional self-directed learning. Time commitment varies depending on prior experience.
Data Science Algorithms runs one evening a week from September 2024 to December 2024, final assessments to due in early January. Data Exploration and Pre-Processing runs two evenings a week from January to March with assessments completed by early May.
Contact hours are synchronous, online, from 6pm to 9pm, and are also recorded. One-to-one support is also available throughout the week.
Timetabled Days: Tuesday and Wednesday.
Applicants can express their interest for this course by completing the form at the link below:
