Overview
Application Timeline
Tuition
- Year 1
| Student categories | Study | |
|---|---|---|
| Full-time | Part-time | |
| England | £9,200 | N/A |
| Northern Ireland | £9,200 | N/A |
| Scotland | £9,200 | N/A |
| Wales | £9,200 | N/A |
| EU | £19,100 | N/A |
| International | £19,100 | N/A |
Requirements
Language requirements information is currently unavailable.
Modules
Modules is currently unavailable
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About
Program Purpose
The MSc in Applied Data Science aims to equip students from non-specialist backgrounds with the skills necessary to thrive in the digital economy.
Key Learning Outcomes
- Understanding and visualizing data
- Encouraging statistical thinking
- Developing data-driven decision-making skills
Foundational Skills
The program provides essential training in:
- Mathematics
- Statistics
- Basic programming skills
Computer Science Topics
Students will gain key skills in:
- Data Visualization
- Machine Learning
Target Audience
This program is designed for students with
...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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