MSc Data Science & Computational Intelligence draft

Program Overview

This master's program in Data Science equips graduates with advanced machine learning techniques and data analysis skills to solve data-driven problems in various industries. Through practical activities, industry input, and an individual research project, students gain expertise in analyzing large datasets, interpreting complex data, and developing innovative computational intelligence applications. The program offers an optional work placement opportunity and prepares graduates for careers as data scientists, data professionals, and data analysts in diverse sectors.

Program Outline

Degree Overview:

Outline:

The program curriculum emphasizes practical activities, industry input, and skill development. Students learn advanced machine learning techniques, neural networks, evolutionary computing, fuzzy computing, data and web mining, Natural Language Processing (NLP), development tools, and platforms. A key feature of the program is the individual research project, which can be either industry-based or conducted with university research groups. This project serves as a platform for applying learned skills and gaining professional data science experience. Past student projects included analyzing data for the movie industry, oil well cost assessment, customer emotion recognition, social media sentiment analysis, scene labeling, object recognition, and elderly care robotics controller design.

Modules:

• Machine Learning (15 credits): Introduces machine learning concepts, algorithms, and applications.
• Data Management Systems (15 credits): Provides a foundation in data management principles and technologies in centralized and distributed environments.
• Introduction to Statistical Methods for Data Science (15 credits): Focuses on widely used statistical methods and their applications in data science.
• Natural Language Processing (15 credits): Covers automated linguistic data processing methods and solutions for real-world text data applications.
• Big Data Analytics and Data Visualization (15 credits): Introduces cutting-edge techniques for uncovering patterns and insights in large datasets.
• Artificial Neural Networks (15 credits): Explores the theoretical and practical aspects of neural networks.
• Modeling and Optimisation Under Uncertainty (15 credits): Provides in-depth knowledge of advanced machine learning concepts in supervised and unsupervised learning.
• Individual Research Project Preparation (15 credits): Guides students in selecting a research topic and supervisor, developing literature review skills, and formulating a research plan.
• Computing Individual Research Project (60 credits): Enables students to undertake an individual research project under supervisor guidance, culminating in a comprehensive report and critical reflection.

Optional Work Placement:

The program offers an optional work placement opportunity for up to 12 months, extending the duration of the master's to 24 months. The placement aims to provide students with industry experience and enhance their employability. Additional fees and eligibility requirements apply.

Assessment:

Assessments vary depending on the module and may include coursework, essays, projects, group work, and formal examinations. The program aims to ensure assessments are fair and assess student progress towards intended learning outcomes.

Teaching:

Teaching methods include lectures, seminars, tutorials, presentations, group projects, workshops, and practical laboratory sessions. The program also embraces emerging technologies in the student experience. Teaching contact hours vary per semester, averaging around 12 per week during the taught semesters. There is a significant element of self-directed study, where students invest around 35 hours per week.

Careers:

Graduates possess the potential to pursue careers in various sectors as data scientists, data professionals, and data analysts. These opportunities can be found in financial services, retail, marketing, customer and business intelligence, scientific research, health and medicine, the retail market, information technology, government, ecommerce, energy, transportation, telecommunications, biotechnology, and pharmaceutical companies.

Other:

• The program incorporates international field trips to various locations (costs vary).
• Students receive support in securing and completing work placements.
• The program features state-of-the-art facilities including Cisco labs, virtual labs, and Games Technology labs.
• International students are eligible for financial support through the EU Support Bursary.
• The program is aligned with the university's assessment strategy for fairness and progress monitoring.
• Students have access to dedicated Talent Team support for career development and placement opportunities.