Courses Offered

COMP4501 Data Science in Discipline Project

2025-26

Instructor(s):

Choi Loretta

(Class A)

No. of credit(s):

Recommended Learning Hours:

Pre-requisite(s):

Co-requisite(s):

Mutually exclusive with:

COMP4502

Remarks:

Course Learning Outcomes

1.	[End-to-End Project Execution] Plan and execute the full lifecycle of a data science project, including problem identification, data collection, exploration, modeling, analysis, and solution delivery, mirroring real-world expectations for Data Science professionals.
2.	[Technical Implementation & Domain Integration] Apply data science methodologies to design and implement practical, data-driven solutions for domain-specific problems, ensuring relevance and addressing real-world needs through interdisciplinary understanding.
3.	[Communication & Documentation] Effectively communicate technical concepts, project progress, and results to stakeholders through verbal presentations, written reports, and live demonstrations, ensuring clarity for both technical and non-technical audiences.
4.	[Decision Making & Problem Solving] Navigate unforeseen challenges in data science projects, make informed decisions under constraints (e.g., data limitations, time, resources), and adapt methodologies to achieve feasible and impactful outcomes.

Mapping from Course Learning Outcomes to Programme Learning Outcomes
	PLO a	PLO b	PLO c	PLO d	PLO e	PLO f	PLO g	PLO h	PLO i	PLO j
CLO 1				T						T
CLO 2	T	T	T	T		T		T		T
CLO 3					T		T
CLO 4									T	T

T - Teach, P - Practice
For BEng(CompSc) Programme Learning Outcomes, please refer to here.

Syllabus

Calendar Entry:
Students will work on a capstone project which is on data science in association with a domain focus. Students are required to identify a data-intensive problem in a specific application domain, and to implement a data-driven solution for the problem. Students will undergo a complete data science project life cycle, from problem understanding, data collection, data exploration to data modelling, analysis and interpretation, and finally deliver a data science solution.

Detailed Description:

Phase 1: Problem Framing	Mapped to CLOs
Phase 1: Problem Framing	1, 2, 3, 4
Phase 2: Data Exploration & Modeling	Mapped to CLOs
Phase 2: Data Exploration & Modeling	1, 2, 3, 4
Phase 3: Solution Deployment & Storytelling	Mapped to CLOs
Phase 3: Solution Deployment & Storytelling	1, 2, 3, 4

Assessment:
Continuous Assessment: 100%

Teaching Plan

Please refer to the corresponding Moodle course.

Moodle Course(s)

Courses Offered

COMP4501 Data Science in Discipline Project

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