UBDC Summer Training 2017: Introduction to Scientific Computing with Python

The Urban Big Data Centre (UBDC) is a research centre and national data service based at the University of Glasgow. We promote the use of big data and innovative research methods to improve social, economic and environmental well-being in cities.UBDC has been jointly funded by the Economic and Social Research Council (ESRC), which is part of UK Research and Innovation (UKRI), and the University of Glasgow since 2014.

Urban Big Data Centre

The <A HREF="http://ubdc.ac.uk/" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">Urban Big Data Centre</A> at the University of Glasgow is pleased to announce the return of our <A HREF="http://ubdc.ac.uk/outreach-plus-training/sasnet/" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">SASNet</A> data skills training programme for summer 2017.
The programme will run from 1st August - 6th September offering an opportunity for skills development in key areas of data analytics, methods, and data management. Please visit <A HREF="http://ubdc.ac.uk/outreach-plus-training/sasnet/summer-training-2017" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">http://ubdc.ac.uk/outreach-plus-training/sasnet/summer-training-2017</A> to view the full selection of courses.
Please contact <A HREF="mailto:keith.maynard@glasgow.ac.uk" TARGET="_blank" REL="nofollow noopener noreferrer">keith.maynard@glasgow.ac.uk</A> with any enquiries about the training programme.
 
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<H2 CLASS="MsoNormal">Introduction to Scientific Computing with Python</H2>
Course instructor: <A HREF="http://www.gla.ac.uk/schools/socialpolitical/staff/yangwang/#/publications,conferenceorworkshopitem" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">Yang Wang</A>, 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
Audience: Social scientists, students, practitioners
Fees:  £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 summary:
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 content:
<UL>
<LI>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;</LI>
<LI> Common data analysis and plotting libraries including NumPy, SciPy, Pandas, Matplotlib, proven to be useful in day-to-day data manipulation practice.  </LI>
</UL>
Payment and registration:
Lunch will be provided in the break room adjacent to the IT lab - please specify any dietary or access requirements when registering. 
Payment by card preferred. 
If you are unable to pay by debit or credit card we are able to accept payment by invoice. Please supply the following information by e-mail to <A HREF="mailto:keith.maynard@glasgow.ac.uk" TARGET="_blank" REL="nofollow noopener noreferrer">keith.maynard@glasgow.ac.uk</A> within 14 days of registering on Eventbrite in order to confirm your place on the course:
<UL>
<LI>Contact name for invoice</LI>
<LI>Purchase Order number (note that the supplier is University of Glasgow)</LI>
<LI>Contact e-mail address for payment correspondence</LI>
<LI>Full name of organisation/department</LI>
<LI>VAT registration (if applicable)</LI>
<LI>Currency</LI>
<LI>Address for Invoice to be sent and telephone number</LI>
</UL>
To cancel your place and request a refund, please email <A HREF="mailto:keith.maynard@glasgow.ac.uk" TARGET="_blank" REL="nofollow noopener noreferrer">keith.maynard@glasgow.ac.uk</A>. Please note that a refund of course fees less 10% administrative charge can only be issued if you cancel your place in writing at least 7 days prior to the course after which time fees will be non-refundable. Substitutes can be made at no extra charge up until 5pm on the last working day before the course.

Jura Teaching Lab, Level 4 Annexe

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UBDC Summer Training 2017: Introduction to Scientific Computing with Python

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UBDC Summer Training 2017: Introduction to Scientific Computing with Python

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