| Unit name | Programming in Business Analytics |
|---|---|
| Unit code | MGRCM0034 |
| Credit points | 20 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
| Unit director | Dr. Zhang |
| 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) |
None |
| Units you may not take alongside this one |
None |
| School/department | School of Management - Business School |
| Faculty | Faculty of Social Sciences and Law |
Why is this unit important?
In today’s data-driven world, the ability to process, analyse, and visualise data efficiently is essential for business success. Traditional tools like Excel are becoming increasingly insufficient for handling large-scale and complex data. Businesses require scalable and versatile solutions to address these challenges, and programming skills are becoming indispensable.
This unit focuses on Python, a programming language renowned for its simplicity, versatility, and ease of learning. Python's intuitive syntax makes it an excellent starting point for beginners, while its extensive ecosystem of libraries, such as Pandas, NumPy, and Matplotlib, provides powerful tools for business analytics. Moreover, learning Python builds a solid foundation for understanding other programming languages, as many of its principles and practices are transferable. By mastering Python, students not only gain the ability to solve real-world business challenges but also develop the confidence to explore and adopt additional programming technologies in the future.
How does this unit fit into your programme of study
This unit is a foundational course that supports the entire programme by equipping students with essential programming skills. Students can develop technical capabilities that are directly applicable to a wide range of business analytics and related tasks. The knowledge and experience gained in this unit provide a solid technical base, enhancing students’ ability to excel in other units such as Data Analytics in Business, Modelling Analytics, and more. By integrating Python into the programme, this unit ensures students are prepared to connect technical and business knowledge, enabling them to solve complex, real-world problems effectively.
An overview of content
This unit teaches students the programming language of Python in business analytics. Students will learn the fundamental knowledge of programming, Python basics, Python for Data Science, Python for Data Visualisation and applications to equip the ability to handle practice business problems.
How will students, personally, be different as a result of the unit
Upon completing this unit, students will gain a solid understanding of fundamental programming principles and concepts within the context of developing solutions for business analytics. They will be equipped with practical knowledge of business analytics tools, enabling them to effectively support descriptive, predictive, and prescriptive analytics.
Learning Outcomes
ILO 1 – Demonstrate a foundational understanding of programming concepts, including variables, data types, control structures, and functions, with a focus on their application in business analytics.
ILO 2 – Utilise Python libraries such as Pandas and NumPy to efficiently clean, preprocess, and manipulate business data.
ILO 3 – Write Python scripts to analyse datasets, calculate descriptive statistics, and identify trends and patterns relevant to business decision-making.
ILO 4 – Create and customise visualisations using libraries like Matplotlib and Seaborn to present analytical results clearly and effectively.
ILO 5 – Design and implement solutions for business analytics challenges by leveraging programming to process, analyse, and interpret data, delivering practical and actionable insights.
The unit will be delivered through a series of exercise lectures with computers (3 hours*10 weeks). Blackboard will be used to engage students with the unit content.
Tasks which help you learn and prepare you for summative tasks (formative):
Feedback to students is provided throughout the unit in the form of formative quizzes, feedback online and in the classroom from tutors in response to student discussions, questions, and ongoing work.
Tasks which count towards your unit mark (summative):
The summative assessment for this unit has both individual (50% of the overall unit mark) and group (50% of the overall unit mark) assessments.
Individual (50%) (ILOs 1-4 covered)
Students need to attend one 60-minute online test (Multiple Choice or Short Answer) via Blackboard. It will cover the topics of Python basics, Python for Data Science and Python for Data Visualisation (Weeks 1-8).
Group (50%) (all ILOs covered)
Students will be working in groups to collect, prepare and analyse real data concerning business by using Python. They are expected to apply knowledge and skills learnt through this unit to support businesses in exploring problems and making operation strategies. Each group will submit one 2,000-word project report and the original coding file.
When assessment does not go to plan
When a student fails the unit and is eligible to resubmit, failed components will be reassessed on a like-for-like basis.
Individual resubmission (50%)
Students need to re-attend one 60-minute online test (Multiple Choice or Short Answer) via Blackboard. It will cover the topics of Python basics, Python for Data Science and Python for Data Visualisation (Weeks 1-8).
Group resubmission (50%)
Students are expected to submit a 1,000-word report/reflection on the original group project.
This report should respond to important comments from the failed initial group report, aligning with ILOs 1-4. They are also expected to discuss challenges presented to them during the project and how they overcame them, ways and opportunities that could have been explored to further improve the performance of their analysis, and reflect on what they learned during the project.
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. MGRCM0034).
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.
