Applied Data Science
Mathematical Sciences
Taught
MSc
Taught
MSc
Overview
Application Timeline
Tuition
- Year 1
| Student categories | Study | |
|---|---|---|
| Full-time | Part-time | |
| England | £10,500 | £10,500 |
| Northern Ireland | £10,500 | £10,500 |
| Scotland | £10,500 | £10,500 |
| Wales | £10,500 | £10,500 |
| Channel Islands | £10,500 | £10,500 |
| Republic of Ireland | £10,500 | £10,500 |
| EU | £22,750 | £22,750 |
| International | £22,750 | £22,750 |
Requirements
Language requirements information is currently unavailable.
Modules
Modules is currently unavailable
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About
The MSc Applied Data Science is a conversion course tailored for students lacking prior university-level mathematics or statistics experience, aiming to engage in the digital economy. It builds on undergraduate degrees in humanities, social sciences, or business studies, equipping students with essential data science skills through practical applications and case studies.
Course Content
The curriculum includes programming in R, text analytics, and the use of relational databases and SQL, focusing on applications relevant to various fields such as humanities, life sciences, and marketing. The course promotes statistical thinking through data...
Subject Area Information
Applied statistics is a dynamic and essential discipline that focuses on the practical application of statistical techniques to solve real-world problems. This field is integral to various industries, including healthcare, finance, marketing, engineering, and social sciences.
1. Introduction to Applied Statistics
2. Statistical Methods for Data Analysis
3. Probability and Statistical Inference
4. Multivariate Analysis
5. Time Series Analysis and Forecasting
6. Statistical Computing and Data Visualization
- Data Analysis
- Statistical Software Proficiency
- Problem-Solving
- Communication
- Critical Thinking
Career
Graduates with a background in applied statistics have a wide array of career opportunities available to them.
Data Analyst
Analyzing data to help organizations make informed decisions.
Statistician
Designing experiments, surveys, and analyzing data to draw meaningful conclusions.
Biostatistician
Applying statistical methods to biological and health-related research.
Market Research Analyst
Studying market conditions to identify potential sales opportunities.
Financial Analyst
Analyzing financial data to guide investment decisions.
Quality Control Analyst
Using statistical methods to ensure product quality and process efficiency.
Actuary
Assessing financial risks using mathematics, statistics, and financial theory.
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