Master of Data Science (Bioinformatics and Biological Modelling)

Program Overview

The Master of Data Science (Bioinformatics and Biological Modelling) at Durham University equips students with the skills to analyze and interpret complex biological data. This conversion course combines data science principles with specialized knowledge in bioinformatics and biological modelling, preparing graduates for careers in fields such as drug discovery, genomics, and precision medicine.

Program Outline

Master of Data Science (Bioinformatics and Biological Modelling)

Degree Overview:

Overview:

The Master of Data Science (Bioinformatics and Biological Modelling) at Durham University is a conversion course designed to equip students with the skills needed to access, clean, analyze, and visualize data in the field of bioinformatics and biological modelling. This program is particularly suitable for individuals with backgrounds in biological or physical sciences or humanities who are interested in pursuing careers in data science but lack a strong data component in their undergraduate studies.

Objectives:

• Enable students to develop quantitative skills in bioinformatics and biological modelling.
• Provide students with a comprehensive understanding of data science principles and practices.
• Equip students with the ability to analyze and interpret complex biological data.
• Develop students' critical thinking and problem-solving skills in the context of bioinformatics and biological modelling.
• Prepare students for successful careers in data science and related fields.

Program Description:

The program combines a strong foundation in data science methodologies with specialized knowledge in bioinformatics and biological modelling. Students will acquire fundamental skills in data analysis, machine learning, and statistics, while also gaining expertise in areas such as genomics, transcriptomics, and protein sequence analysis. The program culminates in a research project where students apply their acquired skills to a specific research problem in biosciences.

Outline:

Program Content:

The program covers a wide range of topics, including:

• Data Science Fundamentals: Introduction to data science, programming for data science, statistical analysis for data science, machine learning, and ethics and bias in data analytics.
• Bioinformatics and Biological Modelling: Bioinformatics, modelling in molecular biology, and analysis of genomic and transcriptomic data.
• Research Methods: Critical perspectives in data science and research project.

Course Schedule:

The program is typically delivered over one year, with the following structure:

• Semester 1: Introduction to Data Science, Programming for Data Science, Statistical Analysis for Data Science, and Critical Perspectives in Data Science.
• Machine Learning: This module introduces students to the theory, computation, and application of machine learning techniques, including decision trees, support vector machines, and neural networks.
• Modelling in Molecular Biology: This module introduces students to the principles of modelling in molecular biology, including the use of mathematical models to simulate biological processes.
• Critical Perspectives in Data Science: This module examines the ethical and societal implications of data science, including issues related to bias, privacy, and the use of data in decision-making.
• Research Project: This module allows students to conduct an independent research project on a topic of their choice related to bioinformatics or biological modelling.

Assessment:

The program is assessed through a combination of coursework, examinations, and a research project.

• Coursework: Students will complete assignments, projects, and presentations throughout the program.
• Examinations: Students will take written examinations at the end of each semester.
• Research Project: Students will be assessed on the quality of their research project report and presentation.

Teaching:

The program is taught by a team of experienced researchers and lecturers from the Department of Natural Sciences. The teaching methods vary depending on the modules, but typically include lectures, seminars, workshops, and practical sessions.

Careers:

Graduates of the Master of Data Science (Bioinformatics and Biological Modelling) program are well-prepared for careers in a variety of fields, including:

• Bioinformatics
• Computational biology
• Data analysis
• Drug discovery
• Genomics
• Machine learning
• Molecular biology
• Pharmaceutical research
• Precision medicine
• Statistical analysis

Other:

The Master of Data Science (Bioinformatics and Biological Modelling) program is offered at Durham University, a top-ranked university located in the historic city of Durham, England. The program is designed to provide students with a rigorous and comprehensive education in data science, bioinformatics, and biological modelling. Graduates of the program will be well-prepared for successful careers in a variety of industries.

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).