The School of Computing and Data Science (https://www.cds.hku.hk/) was established by the University of Hong Kong on 1 July 2024, comprising the Department of Computer Science and Department of Statistics and Actuarial Science and Department of AI and Data Science.

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Courses Offered

COMP3510 Internship (DS&E)

COMP3510 Internship (DS&E)

2025-26
Instructor(s):Chim T W
(Class A) No. of credit(s):0
Recommended Learning Hours:
Pre-requisite(s):  
Co-requisite(s):  
Mutually exclusive with:  
Remarks:

Course Learning Outcomes

1. [Working Experience]
Gain solid, practical experience in a job placement related to the field of data science.
2. [Communication]
Develop effective technical and interpersonal communication skills for engagement with people of diverse backgrounds in a work environment.
3. [Professionalism]
Recognize the responsibilities of data science professionals, and have the commitment to professionalism.
4. [Data science and society]
Able to ask serious questions about the social impact of data science technology and to evaluate proposed answers to those questions.
5. [CPD]
Recognize the importance of continual development as a data science professional.
Mapping from Course Learning Outcomes to Programme Learning Outcomes
 PLO aPLO bPLO cPLO dPLO ePLO fPLO gPLO hPLO iPLO j
CLO 1
CLO 2
CLO 3
CLO 4
CLO 5

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

Syllabus

Calendar Entry:
The course consists of two components: internship and professionalism. Internship requires students to spend a minimum of four weeks employed, full-time, as data science interns or trainees. During this period, they are engaged in work of direct relevance to their programme of study. The Internship provides students with practical, real-world experience and represents a valuable complement to their academic training. Professionalism exposes students to social and professional issues in data science and engineering. Students need to understand their professional roles when working as data science professionals as well as the responsibility that they will bear. They also need to develop the ability to ask serious questions about the social impact of data science technology and to evaluate proposed answers to those questions. Topics include social context of data science, risks, safety and security concerns for data science professionals, professional and ethical responsibilities, and continuing professional development.

Detailed Description:

COMP3510 Internship Mapped to CLOs
Internship placement1, 2, 3, 4, 5

Assessment:
Continuous Assessment: 100%
Teaching Plan

Please refer to the corresponding Moodle course.

Moodle Course(s)

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