| Program start date | Application deadline |
| 2025-03-01 | - |
Program Overview
Higher Diploma in Science in Data Analytics | Full-time
Overview
This programme has been designed to meet the ongoing need for Data Analysts throughout the workforce which can directly create added value and wealth to the Irish businesses and the society. Technological innovation applied to computing has created a wave of disruptive activity that will change the shape of the global information system over the next decade. The purpose of this programme is to provide students with advanced knowledge, critical thinking and computing skills to be able to meet the industry demands.
Aims of the Programme
- Develop learner’s ability to enhance their employment opportunities in Data Science sector.
- Enable learners to progress their ability to demonstrate advanced skills in Data Analytics.
- Develop abilities of an advanced nature in an array of Data Science disciplines.
- Contextualise newly gained practical skills in a real-world environment through placement and project work.
Objectives of the Programme
- Develop learner’s criticality in order to analyse industry trends in Big Data.
- Develop learners who are capable of performing robust, significant reports on the future orientation of the field of data analytics with specific emphasis on the problem domain.
- Provide learners with a platform to develop the requisite technical and design skills required by industry and to deepen knowledge of statistical analysis and analytical models.
- Enable learners to implement scalable Big Data applications.
- Prepare learners to work effectively and collaboratively in the execution of common goals.
- Provide work opportunities where learners can apply knowledge to a real-world situation.
Assessment Methods
Assessment will reflect the applied nature of the programme and will include a combination of ‘take-home’ assignments, skills-based assessments, practical lab tasks, projects, demonstrations and presentations in addition to conventional examinations.
Delivery
All learners are expected to attend in person in class.
Entry Requirements
The minimum entry requirements for the Higher Diploma in Science in Data Analytics are:
- A Level 8 primary undergraduate honours degree with a minimum Pass classification from a recognised third level institution in a non-cognate area and ideally be able to demonstrate mathematical problem solving skills as part of previous programme learning. i.e. math's at Leaving Cert level would suffice.
- Or
- A minimum Level 7 Ordinary Bachelor’s degree in a cognate area such as computer science, technology, networking, information systems, engineering, general science, mathematics, statistics, data science.
- Or
- Applicants who do not have a Level 8 qualification and who have at least 3 years’ work experience may also be considered through the college’s normal RPL procedures. Relevant professional experience may be taken into account and individuals will be assessed on a case-by-case basis through DBS RPL procedures.
Recognition of Prior Learning
Learners may also access this course on the basis of recognition of prior learning or by assessment of prior experiential learning/informal learning. For this particular programme applicants will be considered on a case-by-case basis based upon their educational record, work experience, their ability to demonstrate technical or mathematical problem solving skills and a capacity to successfully participate in the programme.
Course Content
The Higher Diploma in Science in Data Analytics has the following content:
- Advanced Analytics and Web Application
- Applied Data Analytics
- Big Data Managing and Processing
- Data and Network Mining
- Data Visualisation & Communications
- Databases for Business Applications
- Platforms for Data Analytics
- Programming for Data Analytics
- Project
- Statistics for Data Analytics
Structure
Full-time: 1 year (2 semesters of 12 weeks each)
The Full Time Higher Diploma in Science in Data Analytics will run over one academic year from Monday to Friday. Calendars will be available in due course. Please note day time attendance is required on this programme.
Career Opportunities
As the ICT sector continues to grow so too does the demand for skilled personnel in this area. A target of delivering more than 47,000 graduates with high level ICT skills by 2022 has been set by the Government to meet Irelands need for graduates in computing, electronic and electrical engineering. Technology Skills 2022, Ireland's third ICT Skills Action Plan was launched in February 2020 by Minister for Education and Skills Joe McHugh and Minister for Business, Enterprise and Innovation Heather Humphreys.
Roles types that may be suitable for graduates include:
- Senior Data Analyst
- Data Engineering and Analytics
- Financial Analyst
- Power BI Data Analyst
- Consulting: Date Analyst
- Lead Business Analyst
Eligibility
For information on eligibility and funding eligibility requirements, visit the Springboard+ website.
Application Procedures
The application procedures are in 2 stages. First, DBS will contact you in relation to collecting your academic documents to ensure you meet the minimum entry requirements of the programme you have applied for. Then, closer to course commencement, we will contact you again in relation to information on the uploading of the required documentation in order to ensure you meet the Springboard+ Eligibility Criteria.
Next Steps
Apply online via the Springboard portal.
Awarding Body
Quality & Qualifications Ireland (QQI)
Duration
1 Academic Year
Study Mode
Full-Time
Award Level
Level 8 NFQ
ECTS Credits
60
10% Contribution (if applicable)
€725
Next Intake
March 2025
Program Outline
Degree Overview:
Higher Diploma in Science in Data Analytics
Awarding Body:
Quality & Qualifications Ireland (QQI)
Duration:
1 Academic Year (Full-Time)
Study Mode:
Full-Time
Award Level:
Level 8 NFQ
ECTS Credits:
60
Next Intake:
March 2024
Objectives:
The objectives of the program are to:
- Enhance learners' employability in the Data Science sector.
- Enable learners to demonstrate advanced Data Analytics skills.
- Develop advanced abilities in diverse Data Science disciplines.
- Contextualize newly acquired practical skills in a real-world environment through placement and project work.
Description:
This program is designed to meet the increasing demand for Data Analysts with the skills to create value and wealth for Irish businesses and society. Technological innovations in computing are driving a wave of disruptions that will reshape the global information system over the next decade. This program equips students with advanced knowledge, critical thinking, and computing skills to meet these industry demands.
Other:
- The program is designed to be applied in nature, incorporating a mix of assessments, including take-home assignments, skills-based assessments, practical lab tasks, projects, demonstrations, presentations, and conventional summative examinations.
- Learners are expected to attend in person.
- The program is funded by the Human Capital Initiative (HCI) Pillar 1, which covers 90% of the fees for eligible applicants. ## Outline:
Course Content:
- Advanced Analytics and Web Application
- Applied Data Analytics
- Big Data Managing and Processing
- Data and Network Mining
- Data Visualisation & Communications
- Databases for Business Applications
- Platforms for Data Analytics
- Programming for Data Analytics
- Project
- Statistics for Data Analytics
Structure:
- The program runs over one academic year from Monday to Friday.
- Calendars will be available in due course.
- Daytime attendance is required.
Schedule:
- The program runs over two semesters of 12 weeks each.
Modules:
Advanced Analytics and Web Application:
This module introduces students to the principles of Big Data analysis, Big Data platforms, and Big Data programming. Students will gain hands-on experience in using Big Data tools and technologies to analyze real-world datasets.
Applied Data Analytics:
This module covers the essential data analysis techniques used in business intelligence, marketing analytics, and customer relationship management. Students will develop their skills in data manipulation, data analysis, and data visualization using industry-standard software tools.
Big Data Managing and Processing:
This module focuses on the concepts and technologies used to manage and process Big Data. Students will learn about distributed file systems, cloud computing, and data warehousing technologies. They will also gain experience in using tools and techniques for Big Data management.
Data and Network Mining:
This module introduces students to the principles of data mining, web mining, and social network analysis. Students will learn how to extract valuable information from large datasets and use it to make informed decisions.
Data Visualisation & Communications:
This module focuses on the effective visualization of data for communication purposes. Students will learn the principles of data visualization, best practices for creating compelling and informative charts and graphs, and how to use data visualization tools to communicate data insights effectively.
Databases for Business Applications:
This module covers the fundamental concepts of database management systems and their role in business applications. Students will gain hands-on experience with relational databases, SQL, and database administration.
Platforms for Data Analytics:
This module explores various platforms used for data analytics, including cloud-based platforms, open-source platforms, and enterprise platforms. Students will gain experience in using different platforms for data analysis and learn how to choose the right platform for specific data analytics tasks.
Programming for Data Analytics:
This module covers the essential programming skills needed for data analysis. Students will learn the basics of programming using Python, a popular programming language for data analysis. They will also gain experience in using programming libraries and tools for data analysis tasks.
Project:
The project module allows students to apply their knowledge and skills to a real-world problem. Students will work in teams to develop a data analysis project from start to finish, including data collection, analysis, and presentation of results.
Statistics for Data Analytics:
This module covers the fundamental statistical concepts needed for data analysis. Students will learn about descriptive statistics, inferential statistics, hypothesis testing, and regression analysis. They will also gain experience in using statistical software tools for data analysis.
Assessment:
The program uses a variety of assessment methods to evaluate student learning:
- Take-home assignments: These allow students to demonstrate their ability to apply concepts learned in the classroom to real-world problems.
- Skills-based assessments: These assess students' ability to perform specific tasks related to data analysis.
- Practical lab tasks: These provide hands-on experience with data analysis tools and techniques.
- Projects: These allow students to apply their knowledge and skills to a culminating project.
- Demonstrations and presentations: These assess students' ability to communicate their findings effectively.
- Conventional examinations: These assess students' understanding of theoretical concepts related to data analysis. ## Teaching: The program employs a variety of teaching methods:
- Lectures: These provide students with a broad overview of key concepts and theories.
- Tutorials: These provide students with personalized feedback and support in a smaller group setting.
- Practical laboratory sessions: These allow students to apply their knowledge and skills to real-world datasets.
- Guest lectures: These provide students with insights from industry experts.
- Independent study: This allows students to explore topics of interest in greater depth. ## Careers: The program prepares graduates for various careers in data analytics, including:
- Data Analyst
- Data Scientist
- Data Engineer
- Business Intelligence Analyst
- Marketing Analyst
- Customer Relationship Management Analyst Graduates are also well-positioned to pursue further studies in data analytics or related fields. ## Other:
- The program is designed to meet the specific needs of the Irish job market.
- The program is delivered by experienced faculty members with a strong industry background.
- The program provides students with opportunities to network with industry professionals.
- The program prepares students for professional certifications in data analytics.
- The program is offered at a competitive price.
