Principles of Data Science in Python

This module will provide students with the practical tools and techniques required to build, analyse and interpret 'big data' datasets. We will cover all aspects of the Data Science process including collection, munging or wrangling, cleaning, exploratory data analysis, visualization, statistical inference, model building and implications for applications in the real world.
We will look at data manipulating both politically and in the global business industry. We will design testable hypotheses, exploring how data is analysed in meaningful ways by applying suitable experimental methods to determine whether these hypotheses are supported by robust and reliable data. An example of the testable hypotheses that students will be asked to conclude on is: “Do male actors get paid more than females actors?” Students actively analysed medium-large datasets from IMDB statistics to prove/disprove the hypothesis.
During the module, you will work with real world datasets and apply techniques learnt in practical sessions and lectures, to scrape data from the Internet, develop and test hypotheses and present findings. In the laboratory, students will be introduced to the Python programming language including a number of fundamental standard Python libraries/toolkits for Data Scientists including NumPy, SciPy, PANDAS and SCIKIT-Learn, all accessed on Double Screen Computers and high-spec software.
This an introduction course aimed for students wanting to develop a deeper understanding of Python, students should have some mathematical background and an interest in code programming.
The Department of Informatics plays a major role in interdisciplinary research centres at University of Sussex, including the Centre for Computational Neuroscience and Robotics (CCNR), the Centre for Research in Cognitive Science (COGS), the Sackler Centre for Consciousness Science (SCSS) and Sussex Neuroscience.

Course aim

1. Analyse real-world `big data’ datasets using appropriate tools and techniques.
2. Design testable hypotheses and apply suitable experimental methods to determine whether those hypotheses are supported by the data.
3. Evaluate the applicability of different tools and techniques for data analysis and visualisation in different scenarios.
4. Summarise an analysis of big data and present data in an appropriate format.

Credits info

15 EC
All our modules have been formally approved for 15 Sussex credits; equivalent to 7.5 ECTS or 3-4 US credits. This means that your study at Sussex over the summer can count towards your degree.

Sussex modules are accepted for transfer credit towards degrees at most colleges and universities. But policies and degree requirements vary, so you should obtain approval for transfer of module credit before you apply.

Please consult with your study abroad advisor before choosing your modules to ensure you are able to transfer any credit you need.

Fee info

GBP 2605: The full cost of one 3-week Undergraduate Summer School session will be £2605. If you wish to study for both sessions then you can do so.

This is made up of:

Tuition fees of £1,735 per session include:

- All teaching and assessment for one module of study. Where field trips or course excursions are required then the cost of this is included in the tuition fee, however travel costs may be required
- A minimum of 150 study hours, with a minimum of 40 hours class/teaching contact hours
- Modules formally approved for 15 Sussex credits, equivalent to 7.5 ECTS or 3 – 4 US credits
- A transcript of studies upon successful completion of the module (including meeting all attendance and assessment requirements).


The accommodation and campus programme fee of £870 per session include:

- Your own bedroom in on-campus East Slope student village. These are a mixture of en-suite flats and standard flats with shared facilities
- Bedding pack of duvet and duvet cover, sheet, towel, pillow and pillowcase
- Programme of free campus social events and activities throughout each session. Excursions and social programme trips will be provided on Fridays and weekends.

Scholarships

If you are applying from one of our partner institutions, you will be entitled to a reduction in tuition fees. Please contact your study abroad office or summer@sussex.ac.uk for more information.

Register for this course
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