| Program start date | Application deadline |
| 2024-09-01 | - |
Program Overview
The Master of Data Science (Digital Humanities) at Durham University is a one-year conversion course designed for non-quantitative graduates. It equips students with data analysis skills using quantitative and computational methods, focusing on cultural data. The program combines lectures, seminars, workshops, and practical classes with an independent research project, preparing graduates for data science roles in various sectors.
Program Outline
Degree Overview:
Overview:
This Master of Data Science (Digital Humanities) is a one-year conversion course designed to equip students with the skills to analyze large-scale data sets using quantitative and computational methods. It focuses on applying these techniques to cultural data and is well-suited for individuals with a first degree in non-quantitative subjects like humanities.
Objectives:
- Provide students with expertise in accessing, cleaning, analyzing, and visualizing data
- Open career doors in data science for students from non-quantitative backgrounds
- Offer training in contemporary data science from experienced researchers
Program Description:
This interdisciplinary program draws on modules from various university departments. It combines lectures, seminars, workshops, and practical classes with independent research activities. All modules encourage research-mindedness, equipping students with methodological and ethical research skills for future endeavors.
Outline:
Program Content:
- Introduction to social data science: Explores data production, analysis, and ethical considerations.
- Digital humanities theory and practice: Introduces contemporary debates in this field.
- Introduction to data science statistics: Covers essential statistical topics relevant to data science.
- Machine learning: Develop an understanding of essential machine learning concepts and their application.
Structure:
The MDS program consists of core modules, optional modules, and a final research project. The specific modules may vary based on student qualifications and experience.
Optional Modules (examples):
- Introduction to Computer Science
- Introduction to Mathematics for Data Science
- Text Mining and Language Analytics
- Data Exploration, Visualization, and Unsupervised Learning
- Strategic Leadership
- Data Science Applications in Archaeology and Heritage
- Qualitative Approaches to Digital Humanities
- Computer Music
Individual Modules:
- Critical Perspectives in Data Science: Explores data production, analysis, and ethical usage from an anthropological perspective. Focuses on developing ethical and contextual awareness.
- Digital Humanities: Introduces contemporary digital humanities debates, essential technical tools for handling cultural data in digital format, and practical applications of advanced theoretical frameworks and tools.
- Programming for Data Science: Utilizes popular Python software packages for real-world data gathering, manipulation, and process exploration. Introduces data analysis and visualization concepts.
- Statistics for Data Science: Covers statistical fundamentals, including data exploration, statistical models, regression, classification, clustering, and sampling validation techniques.
- Additional Modules (descriptions) These descriptions can be added once you provide specific modules or their names.
Assessment:
Assessment Methods:
A combination of methods is used, including essays, online assessments, individual and group reports, and presentations.
Research Project:
The program culminates in an independent research project under the guidance of a supervisor. This project allows students to apply learned skills to a research problem in their preferred digital humanities domain.
Teaching:
Teaching methods:
A variety of methods are utilized, including:
- Lectures
- Seminars
- Workshops
- Computer labs
Faculty:
Instructors for this program are research-active academics who bring their expertise and real-world experience to their teaching.
Careers:
Career Opportunities:
Graduates are equipped for various data science roles across numerous sectors, including:
- Science
- Humanities
- Health
- Environment
- Social science These sectors are actively seeking individuals with data science expertise, as it transforms how people and organizations live and work.
Other:
- This program is offered by the Natural Sciences Department at Durham University.
- Scholarships and bursaries are available to support students with limited financial resources.
- Facilities include labs, libraries, classrooms, study spaces, networking areas, and social spaces.
Full Time Fees
Tuition fees
Home students £13,500 per year EU students £31,500 per year Island students £13,500 per year International students £31,500 per year The tuition fees shown are for one complete academic year of full time study, are set according to the academic year of entry, and remain the same throughout the duration of the programme for that cohort (unless otherwise stated).
Entry Requirements:
UK Students:
- ANY degree that doesn’t include a strong data science component
- **Candidates with a degree in Arts and Humanities are strongly encouraged to apply.
EU Students:
- Same requirements as UK students.
International Students:
- Same requirements as UK students.
Language Proficiency Requirements:
- Evidence of competence in written and spoken English if the applicant’s first language is not English:
- minimum TOEFL requirement is 102 IBT (no element under 23)
- minimum IELTS score is 7.0 overall with no element under 6.0 or equivalent
Additional Notes:
- The Entry Requirements section only mentions UK, EU, and international students.
- While the course is open to students from all disciplines, those with a background in Arts and Humanities are particularly encouraged to apply.
