UBDC Summer Training 2017: Introduction to Scientific Computing with Python

Wednesday 9 August 2017
10:00 – 16:30 BST
Jura Teaching Lab, Level 4 Annexe, University of Glasgow Library, Hillhead Street, Glasgow G12 8QE

Python with its easy to learn syntax, efficient high-level data structures and extensive standard libraries has becomes a major scientific programming language not only serving as a command-line data exploration environment but also for linking multiple software, tools and databases together to allow for more complex data manipulation and analysis processes.

The course will provide an introduction to Python’s basic concepts and features which will be taught alongside practical, hands-on exercises. Some noteworthy features of the software will be illustrated to provide further understanding of modules, debug and programs.

The course aims to equip participants with the essential scientific data analysInis skills and develop familiarity with some high-level Python libraries including managing data using NumPy, performing mathematical SciPy algorithms, managing numerical tables in Pandas and plotting figures in Matplotlib. You will start gather knowledge and experiences of scripting in Python for some specific data analysis requirements and be prepared for future learning around the wider ranges of Python libraries.

Course instructor

Yang Wang, UBDC, University of Glasgow

Course duration

1 day (Wednesday 9th August 2017, 10:00am – 4:30pm)

Course location

Jura teaching lab, Level 4 Annexe, Glasgow University Library


Social scientists, students, practitioners


  • £35 - For UK registered students
  • £60 - For staff at UK academic institutions, Research Council UK funded researchers, UK public sector staff and staff at UK registered charity organisations
  • £100 - For all other participants

Pre-requisite knowledge

This is an introductory level course so anyone who has an interest in using Python to develop an automated data analysis workflow are welcome. Some basic programming background (enough to understand of logic of programming) would however be helpful.

Course content

  • Python basics including all you need to know to start programming in Python, topics include but not limited to interpreter, control flow tools, data structures, modules, input/output, errors and exceptions, classes, standard library, virtual environments;
  • Common data analysis and plotting libraries including NumPy, SciPy, Pandas, Matplotlib, proven to be useful in day-to-day data manipulation practice.