Course summary
The MSc in Data Science will provide you with the technical and practical skills to analyse the big data that is the key to success in future business, digital media and science.
- The MSc Data Science will prepare you to join a new generation of data scientists that are highly in demand across multiple industries.
- You’ll learn to combine the statistical skills of data analysis and the computational techniques needed to carry out this analysis on a large scale.
- You’ll learn the mathematical foundations of statistics, data mining and machine learning, and apply these to practical, real-world data.
- We’ll equip you with the computational techniques needed to efficiently analyse very large data sets.
- With guidance from industry experts, you’ll put your skills to the test using real-world data to analyse trends in social media, make financial predictions, and extract musical information from audio files.
- You’ll carry out original analysis on real-world data through your final project, which allows you to focus on your specific research interests.
- You’ll use industry-standard software such as Apache Hadoop and Spark to analyse data from industries such as biomedical, financial and social media.
- We have close links with leading industry professionals, who regularly deliver lectures and talks on Data Science.
- You’ll learn from experts in the Department of Computing and the Institute of Management Studies. Many faculty members bring their knowledge from active research and consultancy in a wide range of sectors.
Modules
You will study the following compulsory modules: Data Programming Machine Learning Big Data Analysis Statistics and Statistical Data Mining Data Science Research Topics Final Project in Data Science You will also choose three optional modules up to the value of 45 credits. Examples of recent options include: The User Experience of Artificial Intelligence Artificial Intelligence Neural Networks Blockchain Programming Econometrics Advanced Econometrics From National Statistics to Big Data Marketing Strategy Marketing Analytics Digital Marketing and Branding Natural Language Processing Data Visualisation Critical AI Applied AI for Industry Please note that due to staff research commitments not all of these modules may be available every year.
Assessment method
Taught sessions and lectures provide overviews of themes, which you are encouraged to complement with intensive reading for presentation and discussion with your peers at seminars. Assessments build on lectures and seminars so you are expected to attend all taught sessions to build your knowledge and understanding of your chosen discipline. All assessed work is accompanied by some form of feedback to ensure that your work is on the right track. It may come in a variety of forms ranging from written comments on a marked essay to oral and written feedback on developing projects and practice as they attend workshops.
Entry requirements
We do not assume that you will have programmed before, but we do require a level of mathematical dexterity that is commensurate with having completed a numerate degree. You'll have a BA or BSc Degree at 2.1 level or above in a subject such as computer science, mathematics, statistics, engineering, or quantitative subjects like economics and finance. We accept a wide range of international qualifications. If English isn’t your first language, you will need an IELTS score (or equivalent English language qualification) of 6.5 overall and no element lower than 6.0 to study this programme.
Fees and funding
Tuition fees
No fee information has been provided for this course
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
No additional fees or cost information has been supplied for this course, please contact the provider directly.
Provider information
Goldsmiths, University of London
New Cross
Lewisham
SE14 6NW