Unit name | Data Science |
---|---|
Unit code | ECON30006 |
Credit points | 20 |
Level of study | H/6 |
Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
Unit director | Professor. Davies |
Open unit status | Not open |
Units you must take before you take this one (pre-requisite units) |
Econometrics 1 (EFIM20011) AND Econometrics 2 (EFIM20036) OR Mathematical Programming (MATH20014) OR Applied Quantitative Research Methods (EFIM20010) |
Units you must take alongside this one (co-requisite units) |
None |
Units you may not take alongside this one |
None |
School/department | School of Economics |
Faculty | Faculty of Social Sciences and Law |
The spread of technology means that large amounts of data can be accessed from a desktop computer. This data ranges from real-time measures of economic activity to voting patterns, to local measures of pollution.
This unit explores ways of using large data sets to better understand the societies in which we live. The unit combines methods from programming and economics to work on real world problems.
Students will use Python to access data from on-line sources, GitHub to create on-line repositories, Python or STATA statistical package to analyse and manipulate data, before visualising their final piece of work using HTML, CSS and JavaScript as a live and interactive web page.
Topics include empirical strategy design, fetching and scraping data, data cleaning and storage, as well as the automation of all these tasks. Students will apply concepts of descriptive data analysis as well as econometric techniques learned in the compulsory econometrics courses.
Prospective students should look at the following web pages: Course outline: https://rapidcharts.io/datascience Class of 2022 projects: https://rapidcharts.io/datascience2022
Students will be able to:
Teaching will be delivered through a combination of large and small group classes, supported by online resources
Portfolio of skills (20%), and Data Science project (80%).
All presented as a live webpage, equivalent to 5 pages of A4 (100%)
Assesses all learning outcome
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. ECON30006).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the Faculty workload statement relating to this unit for more information.
Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an
assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.