| TIMETABLE | TEACHING MATERIAL |
| Credits | 20 |
| Level | 5 |
| Semester | 1 |
| Prerequisites | N/A |
| Availability | Available only to MSc Quantitative Finance students |
| Contact | Lectures: 16 | Tutorials: 0 | Labs: 20 | Assignments: 80 | Self study: 84 |
| Assessment | 100% coursework. The assessment will include group work. |
| Resit | TBC |
| Lecturer | Prof Richard Connor, Dr Clemens Kupke |
General Aims
This class aims to provide an overview understanding of some of the (plethora of) technologies used by experts for data analysis, programming and Internet (client-server) systems
Learning Outcomes
After completing this module participants will be able to:
- understand a professional operating system
- different from computers used by the public
- understand how to program in a functional language
- Haskell – just one of many paradigms in common use
- commonly used in financial systems, unusual elsewhere
- understand how to use various tools to interrogate data
- Matlab, Excel
- understand the tradeoffs between tools and programming
- gain detailed knowledge of some technology components
- see close-up the most advanced cloud-based technology in current use
- Google AppEngine and Datastore
Syllabus
- basics of: Linux, data, Excel
- functional programming in Haskell
- basics of MatLab
- Haskell practical exercise
- client-server programming with Java, GWT, AppEngine