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.

Courses Offered

ENGG1202 Introduction to computer science

ENGG1202 Introduction to computer science

2017-18
Instructor(s):Schnieders Dirk
(Class A) No. of credit(s):6
Schnieders Dirk
(Class B)
Recommended Learning Hours:
Lecture: 33.0
Tutorial: 7.0
Pre-requisite(s):  
Co-requisite(s):  
Mutually exclusive with:  
Remarks:

Course Learning Outcomes

1. [Core elements for solving computational problems]
understand the importance of three core elements (discrete mathematics, data structures, and algorithms) for solving computational problems and see how these elements are used to solve the problems via a selected set of real-life problems.
2. [Abstraction]
understand the importance of abstraction and see how to identify and formulate abstract problems from a selected set of real-life examples.
3. [Problem solving]
apply the techniques learned in the course to solve computation problems.
Mapping from Course Learning Outcomes to Programme Learning Outcomes
 PLO aPLO bPLO cPLO dPLO ePLO fPLO gPLO hPLO iPLO j
CLO 1T,P
CLO 2T,P
CLO 3T,P

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

Syllabus

Calendar Entry:
This course introduces a number of real-world computational problems taken from different areas of computer science (e.g. security and cryptography, artificial intelligence, database, web and networking). Through these problems and some hands-on exercises, students are exposed to the mathematics, data structures and algorithms that form the foundations of computer science and see how these elements integrated together to solve those problems.

Detailed Description:

Artificial intelligence Mapped to CLOs
Introduction to computational intelligence with examples on searching, constraint satisfaction problems and related techniques1, 2, 3
Analysis of algorithms Mapped to CLOs
Introduction to the analysis of algorithms with examples on asymptotic analysis, recursion and related techniques1, 2, 3
Image processing and computer vision Mapped to CLOs
Introduction to various computer vision techniques with examples on image enhancement, feature extraction and related techniques1, 2, 3
Cryptography Mapped to CLOs
Introduction to various techniques on secure communication with examples on encryption/decryption, digital signature and related techniques1, 2, 3

Assessment:
Continuous Assessment: 100%

Teaching Plan

Please refer to the corresponding Moodle course.

Moodle Course(s)

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