Data Science, Technology and Innovation

Additional Resources

In addition to the courses already offered on the DSTI programme the University also offers a range of related MOOCs (Massive Open Online Courses)

Data Ethics, AI and Responsible Innovation

Our future is here and it relies on data. Predictive policing, medical robots, artificial intelligences, smart homes and cities - we can all think about how any of those could go wrong. Discover how we can build a future where they are done right.

This story-driven course is taught by the leading experts in data science, AI, information law, science and technology studies, and responsible research and innovation. The course is informed by case studies supplied by the digital business frontrunners and tech companies. It looks at real-world controversies and ethical challenges to introduce and critically discuss the social, political, legal and ethical issues surrounding data-driven innovation, including those posed by big data, AI systems, and machine learning systems. It drills down into case studies, structured around core concerns being raised by society, governments and industry, such as bias, fairness, rights, data re-use, data protection and data privacy, discrimination, transparency and accountability. Throughout the course, it will emphasise the importance of being mindful of the realities and complexities of making ethical decisions in a landscape of competing interests.

Click here to find out more and sign up via EdX

Course Trailer: 

Video: Data Ethics Trailer
Data Ethics Trailer

Data Science in Stratified Healthcare and Precision Medicine

An increasing volume of data is becoming available in biomedicine and healthcare, from genomic data, to electronic patient records and data collected by wearable devices. Recent advances in data science are transforming the life sciences, leading to precision medicine and stratified healthcare.

In this course (which launched in April 2018) you will learn about some of the different types of data and computational methods involved in stratified healthcare and precision medicine. You will have a hands-on experience of working with such data.  You will learn from leaders in the field about successful case studies.

Topics include: (i) Sequence Processing, (ii) Image Analysis, (iii) Network Modelling, (iv) Probabilistic Modelling, (v) Machine Learning, (vi) Natural Language Processing, (vii) Process Modelling and (viii) Graph Data.

Click here to find out more and sign up via Coursera

Additional information is also available in this video:

 

Statistics: Unlocking the World of Data 

At a time where understanding data is becoming more and more important, this course will introduce learners to the fundamentals of statistics, and provide them with a toolkit to better understand the data and statistics we encounter in everyday life.

We will be looking at what data is, how we present it, and how statistics is used to investigate many challenging issues and scientific advances, from global warming to modern-day slavery, or from the decline of biodiversity to advances in pharmaceutical research. Through a combination of videos, examples, interactive apps, discussions and quizzes, you will be taken on a journey into the heart of statistics.

Click here to find out more and to sign up via EdX

Driving Value from Data

The world is awash with data buzzwords, go beyond the hype to explore value.  Developed by the Data Lab, Scotland’s innovation centre for data and AI, this is a course for those setting up data capabilities for the 1st time, or those taking steps to the next level of data maturity. If you are part of a community that is leading the change to make your organisation more data savvy this course is for you.  The main goal of this course is to give learners the confidence to start adding value through better use of data.

By the end of the course, you'll be able to...

  • Describe how organisations use data to drive value.

  • Identify and classify data and opportunities within your own organisation

  • Explain how data mature your organisation is and identify what to do to increase your maturity to align with your ambitions

  • Summarise the main challenges organisations face.

  • Begin to justify the investment required within your own organisation.

Click here to find out more and to sign up via Future Learn

MicroMasters® in Predictive Analytics for Business Applications

There is a growing demand for employees and managers who have experience of Python and machine learning as well as having analytical skills and can make informed decisions that can drive organisational success.

The University of Edinburgh is the first university in the UK to offer a MicroMasters in partnership with EdX. Through this MicroMasters you will be introduced to the major concepts used in a predictive model, learn how to prepare data for modelling, and build predictive models using a range of statistical and machine learning methodologies on a variety of real-life datasets.

Click here to find out more and to sign up via EdX

Click here for further information on how the MicroMasters could be used as a pathway to DSTI

Supercomputing 

Today’s supercomputers are the most powerful calculating machines ever invented, capable of performing more than a thousand million million calculations every second. This gives scientists and engineers a powerful new tool to study the natural world – computer simulation.

Using supercomputers, we can now conduct virtual experiments that are impossible in the real world – from looking deep inside individual atoms, to studying the future climate of the earth and following the evolution of the entire universe from the big bang.

This free online course will introduce you to what supercomputers are, how they are used and how we can exploit their full computational potential to make scientific breakthroughs.

Click here to find out more and to sign up via Future Learn  

Data Science for Ecologists and Environmental Scientists

An online learning initiative for anyone wanting to gain data science skills in the programming language R, with additional content in Python and JavaScript. Our motivation is to overcome "code fear" and "statistics anxiety" in learners of all ages and from all walks of life.

This course is developed for international audiences, but is also uniquely Scottish with real-world data to put quantitative skills into the context of key ecological questions. The three course themes introduce learners to key elements of data science - ‘Stats from Scratch’, ‘Wiz of Data Vis’ and ‘Mastering Modelling’. The 16 individual tutorials that make up the course in addition to the further 25 tutorials hosted by Coding Club allow learners to create their own bespoke learning pathway to gaining key skill sets.

Quizzes and challenges test knowledge, but also allow users to join a larger community of learners and gain confidence in their own skills. Join the hundreds of thousands of Coding Club users and develop your data science skills through this entirely free and engaging online learning initiative.

 Click here to find out more and sign up via Coding Club's webiste 

Additional University of Edinburgh MOOCs

A full list of MOOCs offered throughout the University of Edinburgh in a number of subject areas is available here: 

University of Edinburgh MOOCs