Data Scientist Degree Apprenticeship Bioinformatics BSc (Hons)

Work-based, part-time undergraduate (4 years)

Blended learning, Cambridge

September

Teaching times

Part-time

Trimester 1: One day per week at ARU Cambridge 9:00 - 18:00 plus online study, week commencing 9 September 2019
Trimester 2: One day per week at ARU Cambridge 9:00 - 18:00 plus online study, week commencing 6 January 2020
Trimester 3: Online study, week commencing 27 April 2020

This course is delivered though blended learning: online through Canvas, our learning management system, and attendance at our Cambridge campus.

Overview

Use your knowledge of computing to help answer some of the biggest scientific questions we have left to answer. If you're passionate about coding, programming and algorithms, our Data Scientist Degree Apprenticeship could be your next step.

Full description
The degree apprenticeship is going to help me stand out, because not only do I have a degree - I will also have those years’ experience in a business applying what I have learnt
Josh Greene
ARU Degree Apprentice

Careers

There's a wide range of career opportunities available in the emerging, exciting field of bioinformatics. Plant science, marine bioinformatics, human health, wearable technologies and home genetics testing are just some of the fields you could work in.

Modules & assessment

Year one, core modules

  • Core Biology 1
    Covers a range of topics including the scientific method, experimental design and ethics, basic chemistry for the biosciences, an introduction to genetics and evolution and biodiversity. You will also be inducted into the correct methods of working in a laboratory, including use of risk assessments and health and safety best practice.
  • Introduction to Bioinformatics and Data Science
    Designed to provide a sound knowledge of the context of bioinformatics and data science in relation to biology, computing and software engineering. The wide variety of different areas of study in contemporary bioinformatics will be introduced.
  • Introduction to Biochemistry and Molecular Biology
    The module focuses on consideration of all key aspects of biochemistry and molecular biology: structural and functional biochemistry, enzyme action, kinetics and inhibition, nature and role of antibiotics, metabolism, biochemical techniques, genetic material, the mechanism and control of gene expression and recombinant DNA technology.
  • Mathematics and Statistics for Bioinformatics
    Provides a sound basis in mathematics, statistics and analysis. You will develop a working knowledge of R, and will learn numerical data types. The module covers basic statistical concepts, including: mean; mode; standard deviation and variance. R will be used to explore biological datasets using techniques such as principal component analysis (PCA), regression and correlation analysis.
  • Computational Methods and Algorithms
    Builds sound knowledge of the application of algorithms in bioinformatics. Basic algorithms are introduced via pseudocode. The data-structures required for efficient storage and processing of data will be introduced. Simple worked examples will be used to teach the core algorithms for sequence alignment, clustering and phylogenetics.
  • Introduction to Software Engineering
    Builds on the foundation of basic coding established in ‘Introduction to Bioinformatics and Data Science’ and is designed to introduce you to techniques used in the development of software that are reliable, efficient, useful, and usable. You will gain practical experience developing a software solution to a specific biological problem.

Year two, core modules

  • Foundations of Cell Biology
    Designed to provide an introduction to the cellular basis of life, focusing on their nature and roles of different cell types, including animal, plant and microbial cells. The module provides you with a basic understanding of biological organisation and biochemical processes at the cellular level.
  • Laboratory Techniques for Bioinformatics
    Designed to develop your experience and understanding of techniques that are used to generate bioinformatic data, in both clinical and research settings. You’ll gain experience in a variety of laboratory skills appropriate to the key subjects of bioinformatics and molecular biology, with a focus on gene cloning.
  • Core Biology 2
    Focuses on the history of medicine and an introduction to the biology of disease. Tools to help us diagnose and treat disease, including an introduction to the biomedical science disciplines, aspects of pharmacology; in particular the importance of plant-derived chemicals and technologies incorporating medical physics, are discussed
  • Understanding the Bioinformatics Workplace
    Provides a rich setting for exploration and discovery of a range of knowledge, skills and understanding. Additionally there is the opportunity for you to deepen your understanding of their specific work environment, by undertaking an enquiry using self-directed learning.
  • Bioinformatics Software, Tools and Programming
    Designed to build on the foundation laid in ‘Computational Methods and Algorithms’ and ‘Introduction to Software Engineering’ to expand your ability to use existing bioinformatics tools and frameworks to design and implement pipelines to solve bioinformatics problems.
  • Databases, Management and Analysis
    You will explore the main databases available for the different types of biological entities (DNA, genomes, RNA and proteins), the databases representing biological concepts (eg cladistics, taxonomy and ontology), and other biological databases, including those covering gene expression, protein-protein interactions and orthologues.

Year three, core modules

  • Metabolism and Control
    You will examine a range of metabolic pathways with a view to gaining a detailed understanding of the overall strategy of metabolism and the internal logic of key metabolic pathways. The effects of drugs and inhibitors and the role of allosteric enzymes in the feedback control of metabolism will be also be discussed.
  • Principles of Genetics
    The module starts with a consideration of the classical patterns of inheritance, building on concepts covered in the level 4 module Core Biology 1. Also develop an understanding of the relationship between genotype and phenotype through an integration of concepts at the organismal, cellular and molecular levels.
  • Preparation for Research
    Introduces the concept of independent, self-directed research, giving you the opportunity to design and propose a research project under the guidance of a supervisor. During the process, you will be assigned a supervisor to help and guide them through the process, from the initial concept to the final research proposal.
  • Proteomics and Molecular Structure
    Focuses on molecular structures and their representation, and how this relates to function. You will study and use protein and RNA secondary structure prediction tools and investigate how family and domain databases make use of those tools in large-scale analysis.
  • Advanced Programming Methods for Systems Biology and Visualisation
    Builds on the mathematical, bioengineering, biological and computational material that apprentices will have been taught in previous modules. You will learn how to integrate and apply concepts from the fields of biology, physics, computer science and mathematics to predict and visualise the behaviour of biological systems.
  • Translational Bioinformatics
    Integrates the knowledge and experience gained in the course up to this point and introduces the concept of translating the scientific findings from the laboratory and the results from bioinformatics data analysis into real-world solutions.

Year four, core modules

  • Molecular Cell Biology
    Designed to extend your knowledge and understanding of cell structure, function and disease, at the molecular level, with particular emphasis on the evaluation and discussion of the experimental evidence that has contributed to current concepts, models and treatments.
  • Business Planning and Entrepreneurship
    This module aims to ensure that you develop key employability skills, which are appropriate if you are wishing to embark on a career in bioinformatics research or in industry, with applications to leadership and management.
  • Medical Genetics
    Focuses on the enormous input genetics has had into understanding, and developing treatments for, human disease. Through the study of a wide range of inherited conditions, you will learn to recognise whether single or multiple genes, or major chromosomal changes, are responsible for a particular aberration, and how an underlying genetic change relates to the clinical manifestation of the disease in question.
  • Current Advances in Biomedical Science
    The overall aims of the module are to encourage interest in exciting current research from the biomedical, bio-molecular, and bioinformatics fields, and foster employability with the development of graduate skills, including the use of social media platforms for research and networking purposes.
  • Undergraduate Major Project
    You are required to undertake a final year research project, as a key component of your degree, focused on a topic relevant to your degree field. As part of the research project you will: plan and carry out an independent research project; test an original hypothesis; demonstrate project planning, project execution and hypothesis testing via written and other appropriate skills.

Assessment

On-programme assessments will test the academic elements of your course and may include:

  • essays
  • lab reports
  • case studies
  • presentations
  • in-class tests
  • exams
  • reflective practice
  • practical assessments
  • project proposal and dissertation
  • End Point Assessment.

The End Point Assessment also tests for the apprenticeship element of the course. It's composed of three elements.

  1. A knowledge test, in the format of a multiple choice and open answer exam, to demonstrate your breadth and depth of knowledge of data science and bioinformatics.
  2. A professional discussion (or viva voce) examination. This will involve an in-depth discussion of the major work-based project and your portfolio.
  3. The major undergraduate work-based project (as above) and the production of a dissertation report describing and evaluating the data derived as a result of your research.

Successful completion of the End Point Assessment will signify the completion of the apprenticeship, as well as the full degree.

Where you'll study

Where can I study?

Blended learning
Person using laptop

Study at a time that suits you, using our learning management system.

More about blended learning

Cambridge
Lord Ashcroft Building on our Cambridge campus

Our campus is close to the centre of Cambridge, often described as the perfect student city.

Explore our Cambridge campus

Fees & funding

Course fees

Degree apprenticeships are funded by your employer and the Government

£0

Entry requirements

Loading... Entry requirements are not currently available, please try again later.

  • Full-time employment in a relevant role.
  • 112 UCAS points or equivalent.
  • A level Grade B (or equivalent) in at least one STEM subject, Maths desirable.
  • At least 4 GCSEs at Grade B/Grade 6 which must include Maths and English.
  • If English is not your first language, you will be expected to demonstrate a certified level of proficiency of at least IELTS 6.5 or equivalent.

Applicants who do not meet the above requirements may also be considered on a case-by-case basis.

Similar courses that may interest you

Data Scientist Degree Apprenticeship BSc (Hons)

Part-time, work-based undergraduate (4 years)

Blended learning, Cambridge

September

Artificial Intelligence BSc (Hons)

Full-time, full-time with placement year undergraduate (3 years, 4 year extended, 4 years with placement)

Cambridge

September

Cyber Security BSc (Hons)

Full-time, full-time with placement year undergraduate (3 years, 4 year extended, 4 years with placement)

Cambridge

September

Apply now