Data Science bridges multiple fields including statistics, scientific methods and data analysis to understand data. Essentially it uncovers hidden patterns from raw data using mathematical tools, algorithms and strong interpersonal skills (problem-solving, critical thinking, lots of patience). Every life examples where this field is used include conducting market research to increase customer loyalty, personalising music user playlists, detecting online fraud.
Data Science, by analysing the continuous produced data (million browser searchers and photos uploaded on social media) not only helps train machine learning models but also informs businesses of better decision making processes to maximise profit.
5 main domains make up Data Science:
- Advanced Computing: enhances computing performance and functionality in areas such as semiconductor technologies, programs, computer hardware and software.
- Domain Expertise: encompasses domain knowledge learnt through undergraduate degrees, job experiences but also the ability of data scientist to analyse the industry. Often, they will need to find the right business problem and propose innovative solutions.
- Data Engineering: develops data pipelines that transform collated data so that data scientists and analysts can interpret them. Data engineers create interfaces and mechanisms to make data more accessible.
- Statistics: refers to the mathematical branch which collects, analyses, interprets and presents large numerical data. Statisticians play key roles in scientific discoveries (significance of data), inform decisions based on data analysis and make predictions.
- Visualisation: focuses on presenting the interpreted data and conclusions in the most comprehensive way as possible. Tools such as colour usage, maps and graphs make it easier to identify trends, patterns and outliers in large datasets.
Most common jobs associated to Data Science include:
- Business Analyst: produce detailed business analysis to identify areas which can be improved to benefit customer outreach, addressing market demands and identifying any caveats. They constantly use both their IT and business skills to enhance a business’ efficiency.
Featured Courses
The CPD accredited courses are carefully crafted to help you gain in-depth knowledge on a topic of your interest.
Stem Cell Technology
The field of stem cell technology is a cornerstone of regenerative medicine, offering transformative pathways to repair or replace damaged tissues. This course provides a comprehensive exploration of stem cell biology, from the fundamental differences in cell potency to advanced techniques such as induced pluripotency and direct reprogramming. Participants will gain insight into differentiation protocols, the development of 3D organoid systems, and the application of CRISPR gene editing to correct disease-associated mutations. Beyond the laboratory, the course addresses essential quality control standards, global regulatory frameworks, and the complex ethical landscape of modern biotechnology.
Next Generation Sequencing (NGS)
This intermediate-level course provides a thorough overview of the field of next-generation sequencing, from its properties and strength and its major applications, to an overview of a typical sequencing workflow.
Molecular Ageing
The study of molecular ageing is a cutting-edge discipline, providing a novel lens through which to understand and treat age-related decline. This course offers a comprehensive introduction to the biological drivers of ageing, from evolutionary theories to the molecular hallmarks that define the biological clock. Participants will explore the mechanisms of DNA repair, the impact of oxidative stress, and emerging therapeutic frontiers, including senolytics and rejuvenation technologies moving from the laboratory into clinical consideration.
Cancer Biology: Exploring the Molecular and Genetic Aspects
This is an intermediate-level course that explores the molecular and genetic basis of cancer, its evolution, and cancer immunology.
Neuroscience
Neuroscience is one of the most advanced and fastest growing sciences. The beginning of the 21st century has seen huge developments in techniques to study and understand how the brain works.
CRISPR: Revolutionising Genome Editing
This advanced-level course is designed to develop an understanding of complex concepts related to genomics, particularly CRISPR/Cas technology and its applications...
- Data Scientist: apply and develop methods to analyse as well as visualise data using programming languages (Python, R, C etc). Some tasks to expect include making recommendations to improve current business strategies, identify further opportunities and using acquired skills (modelling, statistics and analytics) for problem solving.
- Data Analyst: understand, interpret and present data to many different entities including pharmaceuticals, banking, private/public businesses and governments. As such they require strong critical analysis, problem solving, numeracy and communication skills.
- Statistician: collects, interprets and displays numerical data to aid companies identify any trends, make any predictions for businesses and validate significance of scientific data. Typical tasks include applying statistical treatments to complex data, convey resulting to non-specialists and designing data acquisition trials.
