University of Aberdeen - Machine Learning for Healthcare

Offered byFutureLearn

Machine Learning for Healthcare
at
FutureLearn
Overview

Develop in-demand data science skills and learn how to apply them in healthcare for a rewarding career in health data science

Duration	14 weeks
Start from	26th Jan'26
Total fee	₹1.46 Lakh
Mode of learning	Online
Official Website	Go to Website
Credential	Certificate

Machine Learning for Healthcare

Table of content

Overview
Highlights
Course Details
Curriculum
Faculty
+ 2 more items

Machine Learning for Healthcare
at
FutureLearn
Highlights

Earn a certificate after completion of the course
CV checks and interview preparation
Discussion boards with your tutors and peers

Machine Learning for Healthcare
at
FutureLearn
Course details

Skills you will learn

R Data Science

Who should do this course?

For those with a background in healthcare or health research who want to learn more about machine learning

It will also be useful for those with a background in computational or data-intensive sciences wanting to work in the health sector

What are the course deliverables?

Describe the machine learning workflow

Explain how machine learning is used to address healthcare problems

Relate a range of healthcare problems to appropriate machine learning algorithms

Discuss current challenges with implementing machine learning in healthcare

Apply machine learning methods using R to address healthcare problems

More about this course

This course explores the intersection of machine learning (ML) and healthcare, providing a comprehensive overview of how advanced computational techniques can be applied to improve patient outcomes, streamline medical processes, and drive innovations in the field

The course covers foundational ML principles and their application in various healthcare contexts, including diagnostics, treatment planning, and personalized medicine

Machine Learning for Healthcare
at
FutureLearn
Curriculum

Supervised and unsupervised machine learning methods

Preparing datasets for machine learning

Evaluating the performance of machine learning algorithms

Theory and implementation of artificial neural networks

Machine learning approaches to natural language processing

Case studies of machine learning applications using health data

The machine learning workflow using the popular data science language R

Technical, ethical and legal challenges in the field

Active areas of research in machine learning

Machine Learning for Healthcare
at
FutureLearn
Faculty details

Dr Caroline Franco

Caroline is a Mathematical Modeller and is a Lecturer in our Institute of Applied Health Sciences. She has worked as an expert modelling consultant in projects commissioned by the World Health Organisation, The Global Fund, and the UK Health Security Agency.