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Computational Health Data Science MSc, PGDip

University of Leicester — Leicester, United Kingdom

Computational Health Data Science MSc, PGDip is a postgraduate Chemistry course at University of Leicester, Leicester, United Kingdom. It takes 12-36 months, costs £25,100 per year and starts in September.

Postgraduate · 12-36 months · Full-time · Chemistry · £25,100 per year

Intakes: September

This course is for you if you want to solve real-world healthcare challenges using data-driven approaches, with effective communication and user-centric approaches to designing solutions. Advanced mathematics or computing skills are not prerequisites, although individuals with backgrounds in mathematical sciences or computing will find opportunities to deepen and further develop their expertise. Computational Health Data Science focusses on designing healthcare apps, creating digital services and developing analytics pipelines. You’ll gain insights into the unique challenges of the healthcare

Modules

  • Statistics for Data Science
  • Fundamentals of Data Science
  • Modelling Data
  • Data Science Research Project
  • Overview of Data Science Practice
  • Interaction Design (ID) and User Experience (UX)
  • Mobile and Ubiquitous Computing
  • Service Design
  • Big Data and Predictive Analytics
  • Information Visualisation
  • Algorithms for Bioinformatics

Frequently asked questions

How long is Computational Health Data Science MSc, PGDip at University of Leicester?

Computational Health Data Science MSc, PGDip takes 12-36 months (Full-time).

How much does Computational Health Data Science MSc, PGDip at University of Leicester cost?

The listed tuition fee is £25,100 per year. Fees can change, so confirm the current amount before you apply.

When does Computational Health Data Science MSc, PGDip start?

Intakes: September.

What level is Computational Health Data Science MSc, PGDip?

It is a postgraduate course in Chemistry.

What will I study on Computational Health Data Science MSc, PGDip?

Modules include Statistics for Data Science, Fundamentals of Data Science, Modelling Data, Data Science Research Project, Overview of Data Science Practice and Interaction Design (ID) and User Experience (UX).