Last places available!
Last places available! 
Optional internship
MSc: 2250 hours
PGDip: 1500 hours
Optional internship
Online
Dual degree
MSc: 180 CAT (90 ECTS)
PGDip: 120 CAT (60 ECTS)
Employability
plan
MSc: £9,588
PGDip: £7,188
Enrolment Fee: £560
This MSc/ PGDip Bioinformatics and Biostatistics prepares you to apply and develop new computational techniques in biomedical research, working both in hospital environments and for companies across the biotech sector.
Our online MSc / PGDip Biostatistics and Bioinformatics will teach you how to use computer tools to store, organise, analyse and interpret vast amounts of data to extract knowledge that can be applied to solving biological and biomedical problems. This course will fully equip you with the skills you need to kickstart your career in this rapidly evolving sector.
You will have access to many hours of audio visual materials, which are essential teaching materials. Thus, you can study wherever and whenever you want.
Approximately twice a week you will carry out practical activities that will be reviewed and evaluated by your specialized teachers.
Class summaries, articles to stay up-to-date... You will have everything you need to keep on learning.
You will learn from well-known experts in the medical sector thanks to our master classes, which you can watch as many times as you want.
At the end of the course you will conduct a research project on a topic of your interest. One of our teachers will supervise your project..
Your teachers will open the doors to
training in MSc / PGDip
Bioinformatics and Biostatistics
with a focus on employability through specialisation:
From the first to the last stage of your training, we will always be by your side to help you make the most of every step.
As soon as you enrol, you will have access to the virtual platform. We will also start your employability plan. Let's get going!
Videos, PDF summaries and live classes from your teachers.
You will regularly test your knowledge to move steadily towards your goals.
You will carry out a bibliographic research project on a topic of your interest.
Let’s get to work! From 60 to 300 hours of optional internships available in a wide range of companies.
You have arrived at your destination! You now have your own CEMP qualification, University of Chichester university accreditation*, and EQAC accreditation*. It's time for new challenges... and new adventures!
*see accreditation conditions.
I want my CEMP certificate! I want my CEMP degree!As your journey progresses, you will discover different modules which will help you, step by step, to reach your final goal.
1. The cell: structure.
2. Cell components and carbohydrates
3. Lipids
4. Peptides
5. DNA
6. ARN
7. Chromosomes
8. Genes and genomes
9. Study of the chromosomes
10. Mutations and polymorphisms
11. Cell division
12. Central dogma of molecular biology
13. DNA replication and repair
14. Transcription
15. Translation
16. Control of gene expression in prokaryotes
17. Control of gene expression in eukaryotes I
18. Control of gene expression in eukaryotes II
19. Epigenetics
20. PCR
21. Recombinant DNA technology
22. Sequencing
23. Nucleic acid hybridisation: arrays
24. Cell mobility and transport
25. Membrane proteins
26. Mass spectrometry
27. X-ray crystallography
28. Protein structure prediction
29. Basic immunology
30. Viruses: structure and function
1. Fundamentals of descriptive analysis of one-dimensional data
2. Introduction to R and RSTUDIO
3. Fundamentals of Probability Calculus I
4. Fundamentals of Probability Calculus II
5. Discrete random variables
6. Continuous random variables
7. Discrete notable distributions
8. Practice of R. Main objects of R
9. Continuous notable distributions
10. Basic elements of a random vector
11. R practice. Representation and simulation of random variables with R
12. Media vector and covariance matrix
13. Estimation of the parameters of a population
14. Confidence range for a proportion
15. Confidence range in normal distributions
16. Hypothesis contrast for a proportion
17. Practice of R. Bias, variance and confidence range for an estimator
18. Hypothesis contrast for a normal population
19. Comparison of populations
20. Practical R. Hypothesis contrast in R
21. The maximum plausibility method
22. The method of linear regression simple I
23. The method of linear regression simple II
24. The model of multiple linear regression
25. Practical R. Linear regression adjustments
26. The model of analysis of variance
27. The method of analysis of covariance
28. Logistic regression
29. Neural networks for regression
30. Variable selection and extraction techniques for regression
31. Variable selection and extraction methods
32. Evaluation of regression models
33. Comparison of regression models
Part I. Python
1. Python, the new unknown
2. Basic data types, operators and input/output
3. Types of advanced data.4. Flow control
5. Function
6. Errors and Object-Oriented Programming
7. Data manipulation
Part II. Omics database and data analysis
1. Introduction to bioinformatics I: Operating System Requirements
2. Introduction to bioinformatics II: How to use the terminal
3. Introduction to omics: application
4. What is massive sequencing? From DNA to NGS data (Big Data)
5. General bioinformatics analysis of mass sequencing data
6. DNA sequencing
7. Integrative Genome Viewer
8. Variant detection through the use of bioinformatics tools
9. Transcriptomics I: RNA-seq
10. Transcriptomics II: Microarrays
11. Characterisation and functional enrichment
12. Other omics
13. Databases: Repositories, data analysis and interpretation of results
14. Bioconductor: repository of bioinformatics tools
15. Practical I: Data analysis using Galaxy
16. Practical II: Designing a pipeline for variant calling
17. Practical III: Designing a transcriptomics pipeline
18. The future of bioinformatics
I am impressed by the amount of knowledge applied in the programme in a very concise way. There are many ways to develop my skills and knowledge. Especially the webinars given by Prof. Alarcón are what I am hooked on. They are very logical, concise, and helpful in organising the learning process. CEMP allows me to develop my skills to the fullest.
I have really enjoyed the course so far - there are good lecturers and well-presented slides. The last few weeks have been more challenging trying to keep up with the workload in between work as well.
I am very impressed and encouraged by the teachers of the course, who are very busy and willing to motivate me, as they use different modes of communication to help me in my learning, especially in an online environment. This is my first online experience, and I'm enjoying it. What I appreciate the most are the online classes and the quizzes and activities at the end of each chapter that made me think and search for the answers, which allowed me to learn more. I also like the flexibility and the course materials, especially the lecture slides.
The programme is excellent. I am delighted that I can access the course at any time and moment. I find the tests and module booklets very helpful for mastering the subject. Dr. Alarcón is an outstanding lecturer, and he has provided me with a lot of assistance. I believe CEMP offers the right programme with all the components that I wanted to learn. But also, the method of the payments (instalments) made it very accessible for me.
I enrolled in the programme because of my interest in bioinformatics, the reputation and excellence of the institution, research opportunities that enhance employability and open diverse career opportunities in academia, industry or research institutions, networking and collaboration, and making significant contributions to the field. Until now, I have had a wonderful experience with CEMP, and I hope it will continue at this level.
Choosing the Postgraduate programme was driven by the perfect fit with my career goals. Initially considering Biostatistics, the inclusion of Bioinformatics was a pleasant surprise, and the freedom to learn remotely sealed the deal. Despite work distractions, the engaging content fuels my determination. Professor Alarcon's insightful teaching style makes complex theories inspiring. The Study Techniques course reveals crucial skills, adding a refreshing, practical dimension to the curriculum.
Why enrol in our MSc / PGDip Bioinformatics and Biostatistics online training programme? Because in addition to having prestigious professors and a curriculum aimed at preventing student drop-out, we guide our students towards achieving their professional goals.
Learn more about the employability plan you'll benefit from the moment you sign up.
The MSc Bioinformatics and Biostatistics unlocks diverse career avenues in biology, healthcare, and data science. Graduates can thrive in biomedical research, clinical trials, healthcare data analysis, genomics, personalized medicine, pharmaceuticals, data analytics, and beyond. Equipped with versatile skills, our graduates are in high demand across industries where data analysis and biological expertise are paramount.
Our MSc Bioinformatics and Biostatistics has a total duration of 2250 hours. This is equivalent to 180 UK credits, the workload typically associated with an academic year. You can also choose our PGDip, which has no Major Project included and has a duration of 1500 hours (120 UK CAT).
Bioinformatics is the application of computational and statistical techniques to study biological data, including DNA, RNA and protein sequences. It involves the development of algorithms and software tools to analyse and interpret large data sets in order to understand biological systems and processes. Bioinformatics has applications in several fields, including genomics, proteomics, drug discovery and personalised medicine.
Biostatistics is the application of statistical methods to study biological data and improve public health. It has many applications, including the design of clinical trials, the analysis of health care data, the identification of risk factors for disease, and the evaluation of public health programmes. Biostatistics also plays a crucial role in developing and testing new medical treatments, and in the analysis and interpretation of epidemiological data to inform public health policy.
At CEMP, we offer online training programmes that are fully adapted to the needs of each person, with tailored payment instalments available worldwide, to make sure each student is able to complete all stages of their MSc / PGDip course successfully. To find out more about fees and payment plans, contact us through the online form and one of our friendly and experienced team will be in touch.
