MSc in Computing (with Major Options)

Program Overview

This MSc in Computing program offers five Major options: Natural Language Processing, Data Analytics, Artificial Intelligence, Secure Software Engineering, and FinTech & Technology and Innovation. It combines theoretical foundations with practical application through projects, preparing graduates for diverse career opportunities in various sectors, including technology, finance, and research. The program features experienced faculty, industry involvement, and excellent teaching and research facilities.

Program Outline

Degree Overview:

Objectives:

This Master of Science (MSc) program in Computing provides graduates with cutting-edge skills to develop high-quality software and systems, addressing business and economic needs. Graduates can pursue either a career path in industry or research and development in academia or the private sector.

Description:

• This MSc in Computing program offers five Major options:
• Natural Language Processing (NLP)
(Full-time only): focuses on developing software for understanding and generating text, with applications in chatbots, virtual assistants, and language translation.
• Data Analytics (DA)
(Full-time and Part-time): delves into analyzing large data sets to extract meaningful conclusions and improve decision-making processes in various industries.
• Artificial Intelligence (AI)
(Full-time only): provides in-depth knowledge of AI principles and techniques for building next-generation AI systems with potential applications in diverse fields.
• Secure Software Engineering (SSE)
(Full-time and Part-time): emphasizes building secure software throughout the development lifecycle, crucial in the modern era of digital security concerns.
• FinTech & Technology and Innovation (FT)
(Part-time only): explores the use of technologies like AI and Blockchain to revolutionize financial services and empower individuals with more control over their finances.
• The program combines theoretical foundations with practical application through projects.
Students choose an area in their Major for which they design and develop a prototype software system addressing a real-world problem.
• Students develop key employability skills for their chosen career path, including software engineering skills, project management, communication, teamwork, problem-solving, research skills, and awareness of social and ethical considerations in their field.

Outline:

Structure:

• Part-time students attend lectures two evenings per week.
• The program culminates in a project practicum, conducted during the summer months, where students typically develop a prototype software system in their chosen Major that addresses a real-world problem.

Content:

• Each Major features specific modules focusing on relevant methodologies, technologies, and applications within that specific field:
• NLP Major:
• Foundations of Natural Language Processing
• Introduction to Machine Learning
• Human Factors in NLP
• Deep Learning for Natural Language Processing
• Advanced Machine Learning
• Data Analytics & Data Mining
• Machine Translation
• Mathematical Methods/Computational Science
• NLP Practicum (30 ECTS)
• DA Major:
• Statistical Data Analysis
• Cloud Technologies
• Data Management and Visualisation
• Mathematical Methods/Computational Science
• Artificial Intelligence, Information and Information Seeking
• Data Analytics and Data Mining
• Machine Learning
• DA Practicum (30 ECTS)
• AI Major:
• Foundations of Artificial Intelligence
• Statistical Data Analysis
• Artificial Intelligence, Information and Information Seeking
• Data Management and Visualization
• Statistical Machine Translation
• Mechanics of Search
• AI Practicum (30 ECTS)
• SSE Major:
• System Software
• Secure Programming
• Cryptography and Number Theory
• Formal Programming
• Concurrent Programming
• Software Process Quality
• Network Security
• SSE Practicum (30 ECTS)
• FT Major:
• FinTech - Financial Innovation (5 ECTS)
• Blockchain: Basics and Applications (7.5 ECTS)
• Statistical Data Analysis (7.5 ECTS)
• Machine Learning (7.5 ECTS)
• High Tech Innovation & Entrepreneurship for FinTech (7.5 ECTS)
• FinTech Practicum (30 ECTS)

Assessment:

• Assessment methods vary depending on the Major and specific module content but typically include a combination of:
• Continuous assessment
• Examinations
• Project work (including presentations)
• Portfolio submissions

Assessment criteria for all Majors include demonstration of:

• In-depth knowledge and understanding of relevant concepts
• Ability to apply theoretical concepts and implement practical solutions
• Strong analytical and problem-solving skills
• Effective communication (both written and oral)
• Teamwork skills and ability to contribute productively within a group
• Research skills (for project work and thesis, if relevant)
• Professionalism and ethical awareness

Teaching:

Methods:

• Teaching methods are tailored to each specific module and may include:
• Lectures and seminars (for theoretical foundations and knowledge building)
• Practical workshops and tutorials (for hands-on skill development)
• Project work (for applying knowledge, developing problem-solving skills, and fostering teamwork)
• Guest lectures from industry professionals (bringing real-world experiences and insights into the classroom)

Faculty:

• The program is delivered by highly experienced and qualified faculty drawn from Dublin City University's School of Computing, featuring experts in each specific Major:
• NLP:
• World-leading academics in NLP with extensive research experience and involvement in relevant research centers like Insight and ADAPT.
• DA:
• Experts in data science, data analysis, and related technologies, with expertise in various industry applications and research fields.
• AI:
• Multi-disciplinary faculty with specialized expertise in AI theory, algorithms, design, development, and applications across diverse areas.
• SSE:
• Faculty with strong research and industry experience in secure software development, programming languages, cryptography, formal methods, concurrency, network security, and related fields.
• FT:
• Faculty with combined expertise in finance, technology innovation, FinTech applications, blockchain technology, data analysis, machine learning, and entrepreneurship.

Unique Approaches:

• Strong emphasis on practical, project-based learning through individual and team projects, fostering application of theory and development of employable skills.
• Close industry involvement through guest lectures, project collaborations, and internship opportunities, ensuring program content remains relevant to current industry demands and prepares graduates for real-world applications.

Careers:

• The MSc in Computing program prepares graduates for diverse career opportunities across various sectors:

Specific Careers per Major:

• NLP:
• Natural Language Processing Specialists
• Machine Learning Engineers
• Data Scientists
• Software Developers (focused on NLP-based applications)
• Research Scientists (NLP)
• DA:
• Data Analysts
• Business Intelligence Analysts
• Data Scientists
• Machine Learning Engineers
• Cloud and Big Data Engineers
• AI:
• AI Developers
• Machine Learning Engineers
• Robotics Engineers
• Computer Vision Specialists
• Research Scientists (AI)
• SSE:
• Secure Software Developers
• Security Architects
• Cryptographic Engineers
• Penetration Testers
• Software Quality Assurance Specialists
• FT:
• FinTech Developers
• Blockchain Developers
• Financial Data Analysts
• FinTech Entrepreneurs
• Investment and Trading Analysts

General Career Opportunities for all Majors:

• Consultancy
• Management
• Leadership Positions
• Research and Development
• PhD studies
• Academic Careers

Industry sectors employing graduates:

• Technology companies
• Financial service providers
• Consulting firms
• Research institutions
• Government agencies
• Healthcare
• Manufacturing
• Retail
• Education
• Many more

Other:

• The School of Computing offers excellent teaching and research facilities, including modern laboratories, computer suites, and high-tech learning spaces.
• Graduates have consistently high employment rates, with many securing positions in leading national and multinational companies.
• The program provides an excellent foundation for further research in a PhD program for those interested in pursuing an academic or research-focused career.

Tuition Fees and Payment Information:

Full time EU Status Fee €7,500 Non EU Fee. €25,000 Part time EU Status Fee Part-time See Modular Fees