Unit information: Introduction to Coding in 2029/30

Please note: Programme and unit information may change as the relevant academic field develops. We may also make changes to the structure of programmes and assessments to improve the student experience.

Unit name Introduction to Coding
Unit code ECON10007
Credit points 20
Level of study C/4
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Professor. Wang
Open unit status Not open
Units you must take before you take this one (pre-requisite units)

None

Units you must take alongside this one (co-requisite units)

ECON10006 - Statistical Methods
EFIM10023 - Mathematics for Economics

Units you may not take alongside this one

None

School/department School of Economics
Faculty Faculty of Social Sciences and Law

Unit Information

Why is this unit important

Programming and coding in a range of languages is increasingly becoming a key demand in the workplace. This unit provides you with the foundations, that you can build upon across your undergraduate study, and will allow you to develop key skills that are important both to employers, and to your future study of data science.

How does this unit fit into your programme of study

Positioned in the second term of the first year, this unit builds upon foundational economic theories and quantitative methods introduced in the first year. It equips you with practical coding skills, preparing them for advanced econometric courses and research projects in the final year.

Your learning on this unit

Overview of content

  • Introduction to programming concepts using Python
  • Data structures and algorithms relevant to economic data
  • Data collection, cleaning, and management techniques
  • Statistical analysis, simulations and hypothesis testing
  • Data visualization methods
  • Application of coding skills to real-world economic issue

How will students, personally, be different as a result of the unit

You will develop the ability to approach economic problems computationally, enhancing their analytical skills. You will gain confidence in handling large datasets, performing statistical analyses, and presenting findings effectively.

Learning Outcomes

By the end of the unit, you will be able to:

  1. Apply programming skills to solve economic problems.
  2. Efficiently manage and process economic data for analysis.
  3. Create visualizations to communicate economic data insights.
  4. Apply coding techniques to empirical research.
  5. Communicate research findings from computational analysis of economic data

How you will learn

Students will be taught through a combination of large group lectures, computer-lab sessions in smaller groups, and independent study.

How you will be assessed

Tasks which help you learn and prepare you for summative tasks:

  • Weekly coding exercises with feedback
  • Group discussions on coding challenges
  • Lab sessions focusing on practical applications

Tasks which count towards your unit mark (summative)

  • Project report (Max 4 pages of text plus appendix of codes, tables and graphs) (50%) (ILO 1 - 5)
  • 120 minute examination (50%) (ILO 1-4)

When assessment does not go to plan

If students fail the unit such that credit points cannot be awarded at the first attempt, they will normally be provided reassessment in the failed element(s).

The reassessment tasks will be:

  • Project report (Max 4 pages of text plus appendix of codes, tables and graphs) (50%) (ILO 1 - 5)
  • 120 minute examination (50%) (ILO 1-4)

Resources

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. ECON10007).

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 University Workload statement relating to this unit for more information.

Assessment
The assessment methods listed in this unit specification are designed to enable students to demonstrate the named learning outcomes (LOs). Where a disability prevents a student from undertaking a specific method of assessment, schools will make reasonable adjustments to support a student to demonstrate the LO by an alternative method or with additional resources.

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. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates within the Regulations and Code of Practice for Taught Programmes.