PolyU MM1041: Introduction to Artificial Intelligence and Data Analytics in Business — course overview with AskSia
PolyU MM1041 — Build foundations in AI, data analytics and Python with business applications, Hong Kong contexts and attention to ethics, privacy and responsible data governance.
Try the original practice example, then use your permitted course materials to check each step with Sia.
Sharpen your argument
A fictional script uses sum([10,20,30])/2 to calculate the average of three sales values. Fix it. Choose the strongest starting point.
The denominator must match the number of observations: values=[10,20,30]; average=sum(values)/len(values).
Check an empty list before division and decide how missing or invalid observations should be handled. This original drill is not an assignment solution.
The weaker choice: Programming skill grows through predicting behaviour and testing small cases. Reading a solution without running or tracing it can hide gaps in your understanding. watch this!
One exam decides 40% of your grade. This whole page is built around that.
Overview
What MM1041 is, and where it sits
Build foundations in AI, data analytics and Python with business applications, Hong Kong contexts and attention to ethics, privacy and responsible data governance.
The public form specifies an exam, without identifying its duration or current timetable. Exclusion: LGT1041. Follow the current subject instructions for submission and permitted tools.
Public source version: Subject description, August 2025. Study advice and practice below are AskSia-authored.
Always treat your own course outline and the exam timetable as authoritative.
Difficulty & time commitment
Is MM1041 hard, and how much time does it take?
Programming skill grows through predicting behaviour and testing small cases. Reading a solution without running or tracing it can hide gaps in your understanding.
Is this course for you
Who tends to do well, and who tends to struggle
You will likely do well if
- Trace variables before running a short program.
You may struggle if
- Programming skill grows through predicting behaviour and testing small cases. Reading a solution without running or tracing it can hide gaps in your understanding.
- Explain how the output supports a business decision and where it may mislead.
Syllabus
The 5 topics, topic by topic
Topics from the public source. Their order is a content map, not an official weekly timetable or published exam weighting.
T1 · AI concepts, machine learning and applications
Public course descriptionT2 · Big data, cloud computing and analytics
Public course descriptionT3 · Data governance, privacy and cybersecurity
Public course descriptionT4 · Python variables, expressions and conditionals
Public course descriptionT5 · Loops, strings and lists
Public course descriptionHow it's assessed
Assessment structure
| Component | Weight | Format & timing |
|---|---|---|
| Participation | 15% | Published component; Subject description, August 2025. Confirm in current course outline. |
| Individual assignment | 15% | Published component; Subject description, August 2025. Confirm in current course outline. |
| Group assignment | 30% | Published component; Subject description, August 2025. Confirm in current course outline. |
| Exam | 40% | Published component; Subject description, August 2025. Confirm in current course outline. |
- The public form specifies an exam, without identifying its duration or current timetable. Exclusion: LGT1041. Follow the current subject instructions for submission and permitted tools.
This is a coursework course. Coursework carries 60% of the grade and the exam is the single heaviest piece at 40%, so steady work across the semester decides your result more than any one sitting.
Final exam timing: Check the current course outline. Confirm the exact date and venue on your exam timetable.
How to actually pass it
A weekly rhythm, two checklists, and the traps to avoid
The course rewards consistency over cramming, and practice over re-reading. Here is the loop that works, then what to have nailed before each exam.
The weekly loop
Before the mid-semester checklist
- Check the current source version and task brief.
- Explain the main concept without copying the wording.
Before the final heaviest topics
- Review your assumptions and evidence.
- Check the current submission and permitted-use rules.
The mistakes that cost marks
Skipping the assumptions. Programming skill grows through predicting behaviour and testing small cases. Reading a solution without running or tracing it can hide gaps in your understanding.
Formula & concept sheet
The vocabulary and formulas you must own
- Variable
- A name referring to a value in a program.
- Iteration
- Repeated execution of a set of instructions.
- Data governance
- Arrangements for responsible management and use of data.
Where it fits
Prerequisites, related courses & why it matters
No prerequisite statement obtained from the public source used here.
Your MM1041 study toolkit
Study the course with Sia, not just read about it
Use your permitted course notes with these study tools. Follow your course’s rules for AI and assessed work.
FAQ
Frequently asked questions
What does MM1041 cover?
Build foundations in AI, data analytics and Python with business applications, Hong Kong contexts and attention to ethics, privacy and responsible data governance.
What makes MM1041 challenging?
Programming skill grows through predicting behaviour and testing small cases. Reading a solution without running or tracing it can hide gaps in your understanding. This is AskSia’s editorial analysis, not a university difficulty rating.
How is the course assessed?
The public source lists Participation (15%), Individual assignment (15%), Group assignment (30%), Exam (40%). The public form specifies an exam, without identifying its duration or current timetable. Exclusion: LGT1041. Follow the current subject instructions for submission and permitted tools.
What should I do before the course starts?
Trace variables before running a short program. Then check the current outline for required preparation, readings and deadlines.
How can I use AskSia for this course?
Open the linked AskSia course study guide to explore its available resources. Use your permitted notes to practise explanations and check your own reasoning; follow the current course rules for AI and assessed work.
Study MM1041 with Sia
Practise explaining the course concepts and check your reasoning. Confirm assessed-work requirements in your current outline.
Start studying with Sia
