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MSc in Data Science - Enrolling Now for April 2024 intake

Enrolling now for April 2024 intake

Data Science Institute


£6,950 inc VAT
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Fee discounts and instalment plans available to eligible candidates.

Study method
Online + live classes
Course format What's this?
Video with subtitles
12 months · Part-time or full-time
MSc in Data Science
Postgraduate What's this?
Additional info
  • Tutor is available to students

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The MSc in Data Science has been designed to develop skills and knowledge in maths, statistics and programming and provide a career path for those who wish to develop their academic, practitioner, research and critical thinking capabilities within the field of data science. As a result, students develop the full set of skills required for data scientists by organisations across multiple industries and sectors globally.

The MSs in Data Science is credit-rated at postgraduate level on the European Qualifications framework and carries 90 ECTS credits.


MSc in Data Science
Awarded by Woolf University


You are provided with highly structured and detailed course content. The full MSc Data Science consists of ten modules covering core skills and knowledge, culminating in a 30 ECTS credit Postgraduate Major Project. The course combines self paced learning with scheduled live online lectures, tutorial support for exam preparation. All students are assigned a supervisor for their major project.


Exploratory Data Analysis

Programming in Python, R and SQL

Data management

Measures of central tendency and variation

Bivariate relationships

Data visualisation

Statistical Inference

Principles of statistical inference

Parametric tests

Non-parametric tests

Analysis of variance (ANOVA)

Fundamentals of Predictive Modelling

Predictive modelling principles

LInear regression models

Model validation

Python and R packages for predictive modelling

Advanced Predictive Modelling

Logistic regression


Survival analysis

Cox regression

Poisson regression

Time Series Analysis

Time Series concepts

Assessing stationarity

ARIMA, ARCH, GARCH modelling

Panel data regression

Unsupervised Multivariate Methods

Principal Component Analysis

Factor Analysis

Multidimensional Scaling

Cluster Analysis

Machine Learning 1

Naive bayes

Support Vector Machines

K nearest neighbours

Machine Learning 2

Decision Tree

Random Forest

Association Rules

Neural Networks

Text Mining and Natural Language processing

Structured and unstructured data

Text mining in R and Python

Natural language processing

Postgraduate Major Project

The Postgraduate Major Project completes the MSc Data Science and students choose a problem from a particular business or social domain. They have the option of working on a real-world problem from their own organisation and work with a mentor in conjunction with their course supervisor.

Students are required to solve a research problem that involves carrying out exploratory data analysis, hypothesis testing, research design and usie a range of classical and/or modern machine learning modelling methods to predict outcomes and provide actionable insights and recommendations. In doing so they will apply technical capabilities together with research skills and critical thinking. A key part of the project is to communicate the output of the student’s research to both technical and non-technical audiences through written, verbal and visual means.

Who is this course for?

  • Graduates from numerate disciplines including business and finance, computing, economics, the sciences, social sciences
  • Data Analysts looking to move into a data scientist role
  • Master’s and PhD graduates and researchers from other disciplines
  • Data science professionals looking to confirm and extend their skills
  • Experienced managers and leaders seeking to gain insight into data science and its role in business and organisations
  • Data science professionals looking to confirm and extend their skills and move into leadership roles


  • An undergraduate degree or equivalent in any discipline.
  • Other professional qualifications at level 6 in a numerate discipline such as accounting, finance, IT, computing.
  • Candidates without a degree but with at least two years' relevant experience may also apply

Career path

  • Graduates of the MSc in Data Science enhance their employability through the technical, research, critical thinking and communication skills that they develop on the MSc.


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Study method describes the format in which the course will be delivered. At Reed Courses, courses are delivered in a number of ways, including online courses, where the course content can be accessed online remotely, and classroom courses, where courses are delivered in person at a classroom venue.

CPD stands for Continuing Professional Development. If you work in certain professions or for certain companies, your employer may require you to complete a number of CPD hours or points, per year. You can find a range of CPD courses on Reed Courses, many of which can be completed online.

A regulated qualification is delivered by a learning institution which is regulated by a government body. In England, the government body which regulates courses is Ofqual. Ofqual regulated qualifications sit on the Regulated Qualifications Framework (RQF), which can help students understand how different qualifications in different fields compare to each other. The framework also helps students to understand what qualifications they need to progress towards a higher learning goal, such as a university degree or equivalent higher education award.

An endorsed course is a skills based course which has been checked over and approved by an independent awarding body. Endorsed courses are not regulated so do not result in a qualification - however, the student can usually purchase a certificate showing the awarding body's logo if they wish. Certain awarding bodies - such as Quality Licence Scheme and TQUK - have developed endorsement schemes as a way to help students select the best skills based courses for them.