Master of Science in Computer Science (Data Science)

Integrated Masters with deeper specialization and research focus
Taught in English
Duration 1 Years
Mode On Campus
Level Postgraduate
Degree Masters Degree
Next Intake TBA

Course Overview

The Master of Science in Computer Science (Data Science) at Technological University Dublin is your gateway to mastering the intricacies of big data and extracting valuable insights. This postgraduate degree is meticulously crafted for aspiring data scientists and analysts eager to build profound technical expertise in areas such as probability and statistical inference, machine learning, and data mining. You will acquire essential skills in data management and visualisation, preparing you to address a wide spectrum of challenges within a field that thrives on data-driven decision-making and continuous innovation.

You will study this on-campus Masters degree full-time over one year, engaging deeply with specialist core modules and critical skills development. The curriculum features a substantial research project or team project, enabling you to apply your acquired knowledge to real-world scenarios. Through modules like Deep Learning and Programming for Big Data, you will cultivate practical competencies and advanced problem-solving abilities. Graduates are well-prepared for impactful roles in data analysis, machine learning engineering, and data science across diverse industries, equipped with the skills to drive progress.

Course Curriculum & Details

Detailed information for serious evaluators

Program Overview

This Master of Science in Computer Science program with a specialization in Data Science equips students with advanced knowledge in probability, statistical inference, machine learning, data management, mining, and visualization. The curriculum emphasizes critical research skills, including scientific literature review, research methods, and proposal writing, culminating in a significant research project or dissertation. Students can further tailor their studies by selecting from a diverse range of option modules covering areas such as geographic information systems, deep learning, and social network analysis.

1 Specialist Core Modules

Probability & statistical inference
Machine learning
Working with data
Data management
Data mining
Data visualisation

2 Critical Skills Core Modules

Research writing & scientific literature
Research methods and proposal writing
Research project & dissertation or team project

3 Option Modules

Geographic information systems
Universal design
Programming for big data
Problem solving, communication and innovation
Social network analysis
User experience design
Deep learning
Speech & audio processing

4 Additional Option

Cost & Affordability

A clear picture of what this course will cost you

Program Costs

First Year Fee Tuition fee
USD 25,586.00
Total Program Cost Estimated total tuition
USD 25,586.00

Currency note: Program costs shown in USD based on the available tuition breakdown.

Living Costs

Accommodation
USD 644.00 - USD 3,372.00
Food & Groceries USD 3,930.00 - USD 5,613.00
Transport USD 842.00 - USD 1,965.00
Utilities & Bills USD 1,404.00 - USD 2,105.00
Estimated Total USD 6,176.00 - USD 9,683.00

Living cost estimates are based on Grangegorman Campus.

Outcomes & Employability

What happens after you graduate

86%
Graduate Employment Rate Within 6 to 12 months of graduation

Common Graduate Roles

Clinical & Medical ServicesCloud Computing & InfrastructureCorporate Finance & TreasuryCybersecurityCybersecurity & Network SecurityFinancial Technology (Fintech)Nursing & Allied HealthPharmacovigilance & Drug SafetyRehabilitation & PhysiotherapySoftware Development & Engineering

Top Employers Hiring for this course

Accenture

Dell Technologies

Microsoft

Optum

Why Study Master of Science in Computer Science (Data Science) at Technological University Dublin

What makes this program stand out

Top 20 in UK For Computer Science

Exeter's Computer Science department consistently ranks among the top 20 in the UK for both teaching quality and research output.

Fast Offers Quick turnaround

Exeter typically responds to applications within 2-3 weeks, giving you clarity on your options quickly.

Flexible Intakes September start

Primary intake in September with January start available for some pathways through the INTO foundation program.

Accredited Industry recognized

Accredited by BCS, The Chartered Institute for IT, meeting requirements for Chartered IT Professional (CITP) status.

Life at Technological University Dublin in Ireland

What daily life looks like for international students

Language

English

Primary language everywhere

Climate

Mild & Rainy

10-20°C average, pack layers

Safety (Numbeo Safety Index)

Very Safe

Exeter is one of UK's safest cities

Frequently Asked Questions

Common questions about Master of Science in Computer Science (Data Science) at Technological University Dublin

Can I work while studying?

International students can work up to 20 hours per week during the term and up to 40 hours during breaks. There’s no separate work permit required for students in full-time programs.

What English language score do I need for this course?

Applicants must meet specific English language requirements. Acceptable tests include Duolingo, TOEFL, IELTS, and PTE, each with defined scores for different components.

What jobs can I get after studying this course?

Graduates can pursue careers as data analysts, machine learning engineers, data scientists, or big data specialists.

What will I actually study in this course?

This program focuses on big data, statistical inference, and machine learning, providing essential skills for aspiring data scientists. You'll engage in practical modules and a substantial research project, enhancing your real-world problem-solving abilities.

When can I start — what are the intake months?

The Master of Science in Computer Science (Data Science) program at Technological University Dublin has an intake month of September each year. Ensure you prepare your application and required documents in advance.
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