Master of Data Science (Health) draft

Program Overview

The Master of Data Science (Health) at Durham University is a one-year conversion course for non-quantitative backgrounds, equipping graduates with the skills to analyze data in healthcare. The program covers topics like statistical analysis, machine learning, and health informatics, preparing students for careers in research, public health, and clinical practice. Graduates are equipped to make a positive impact in healthcare through data-driven insights.

Program Outline

Master of Data Science (Health) G5P323 - Durham University

Degree Overview:

Overview:

The Master of Data Science (Health) is a one-year conversion course designed for individuals with non-quantitative backgrounds who want to pursue a career in data science. It equips graduates with the quantitative skills necessary to effectively analyze data in the fast-moving field of health. This program is particularly relevant as data plays an increasingly crucial role in improving healthcare outcomes and providing tailored care for individuals.

Objectives:

• Develop quantitative skills for data analysis in the health sector.
• Equip graduates to make a significant difference in the field of health through data analysis.
• Bridge the gap between non-quantitative backgrounds and quantitative data science skills.

Description:

The Master of Data Science (Health) draws upon diverse data sources to provide graduates with the knowledge and skills to analyze interactions between people and their environment in the context of health. This program emphasizes the practical application of data science techniques in healthcare and prepares graduates for careers in research, public health, and clinical practice.

Outline:

Content:

The program covers a wide range of topics, including:

• Statistical analysis
• Machine learning
• Data modeling
• Health informatics
• Clinical intelligence
• Public health data analysis
• Health economics modeling
• Survival analysis
• Epidemiological methods
• Data ethics and governance

Structure:

The program consists of core modules, optional modules, and a research project. The core modules provide a foundation in data science, while the optional modules allow students to specialize in areas of interest. The research project allows students to apply their acquired skills to a specific topic in health or social care.

Course Schedule

• Semesters: 2 semesters per year
• Typical Weekly Schedule: A mix of lectures, seminars, workshops, and computer labs.
• Independent Study: Significant time dedicated to independent study, research, and analysis.

Modules:

• Introduction to Statistics for Data Science
• Models and Methods for Health Data Science
• Health Informatics and Clinical Intelligence
• Critical Perspectives in Data Science
• Data Science Research Project
• Optional modules (examples):
• Introduction to Computer Science
• Introduction to Mathematics for Data Science
• Programming for Data Science
• Text Mining and Language Analytics
• Data Exploration, Visualisation and Unsupervised Learning
• Strategic Leadership
• Machine Learning
• Computational Social Science
• Society, Health and Wellbeing
• Ethics and Bias in Data Analysis

Assessment:

• Essays
• Online assessments
• Reports
• Presentations (individual and group)
• Research project

Grading:

Pass/Fail

Teaching:

• Learning methods: Lectures, seminars, workshops, computer labs, independent study, research, analysis, case studies
• Faculty: Research-active staff with expertise in data science and health
• Teaching approach: Emphasis on research methods, skills, and ethics
• Unique features:
• Interdisciplinary program spanning multiple departments
• Focus on real-world applications of data science in healthcare
• Research project opportunity to apply learned skills to a specific area of interest

Careers:

• Career opportunities:
• Data analyst
• Data scientist
• Public health researcher
• Clinical informatician
• Health economist
• Epidemiologist
• Potential sectors:
• Healthcare
• Government
• Research
• Public health
• Pharmaceutical companies
• Graduates are prepared to make a positive impact in the field of healthcare through data-driven insights.

Other:

• Program duration: 1 year full-time
• Start date: September
• Location: Durham City
• Program code: G5P323
• Tuition fees: £13,500 per year for UK students, £31,500 per year for EU/International students
• Scholarships and bursaries available

Conclusion

The Master of Data Science (Health) program at Durham University offers a comprehensive and rigorous curriculum designed to provide students with the knowledge and skills necessary to thrive in the growing field of data science in the healthcare sector. The program emphasizes practical applications, research methods, and ethical considerations, preparing graduates for successful careers in various healthcare-related fields.

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).