MSc Data Science
- Country United Kingdom
- Course Duration 12 month
- Course Type Full Time
- Courses Campus On Campus
- Language Specification IELTS
- Program Level Post-Graduate
- Education Required Graduate
- Admission intake MAY
- Minimum GPA 5
Application Charges
| Application Fee | Tution Fee |
|---|---|
| Free | GBP 17,900 |
Application Date
| Application Start Date | Application Closing Date |
|---|---|
|
2022-11-08
|
2022-12-31
|
Program Description
Data is everywhere. As the volume and complexity of data collected continues to grow, there is increasing demand for expertise in data science to support the analysis and visualisation of all this information.- The MSc Data Science is a conversion course for graduates from a wide range of disciplines and backgrounds looking to pursue a career, or upskill, in this new and rapidly developing field. Data Scientists are in short supply and there is high demand for data science skills across sectors including business, government, healthcare, science, finance, and marketing.
- The aim of the MSc in Data Science is to support students with little previous experience of data analysis or computer programming and to help them to gain new skills such as working with databases; statistical thinking; programming in high-level languages; modelling; applying data science tools and packages; machine learning; information retrieval; data visualisation and addressing the challenges of big data.
- The MSc Data Science is a conversion course for graduates from a wide range of disciplines and backgrounds looking to pursue a career, or upskill, in this new and rapidly developing field. Data Scientists are in short supply and there is high demand for data science skills across sectors including business, government, healthcare, science, finance, and marketing.
- The aim of the MSc in Data Science is to support students with little previous experience of data analysis or computer programming and to help them to gain new skills such as working with databases; statistical thinking; programming in high-level languages; modelling; applying data science tools and packages; machine learning; information retrieval; data visualisation and addressing the challenges of big data.
