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.

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Courses Offered

COMP3522 Real-life data science

COMP3522 Real-life data science

2024-25
Instructor(s):Choi Loretta
(Class A) No. of credit(s):6
Recommended Learning Hours:
Pre-requisite(s):ENGG1330
Co-requisite(s):  
Mutually exclusive with:  
Remarks:

Course Learning Outcomes

1. understand the data science workflow, including identifying business problems, understanding data sources, data cleaning and preparation, exploratory data analysis, modeling, and communication of results.
2. apply the principles of data science to real-world scenarios by designing and executing data-driven experiments, and iteratively refining their approach based on the results, and effectively communicating their findings
3. identify issues in the data science workflow, such as data quality, ethical considerations, and limitations of the models, and develop strategies to address them
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

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

Syllabus

Calendar Entry:
In this course, students will learn data science step by step through real analytics example: data mining, modelling, tableau visualization and more. Unlike many classes where everything works just the way it should and the training is smooth sailing, this course will give students a data science odyssey through experiencing the pains a data scientist goes through on a daily basis. Corrupt data, anomalies, irregularities, etc. Upon completing this course, the students will enhance their data wrangling skills and learn how to 1) model their data, 2) curve-fit their data, and 3) how to communicate their findings. The students will develop a good understanding of Tableau, SQL, SSIS, and Gretl that give them a safe ride in data lakes.

Detailed Description:

Project Mapped to CLOs
Problem Identification1, 2
Implementation1, 2, 3
Demonstration & Presentation1, 2, 3

Assessment:
Continuous Assessment: 100%
Teaching Plan

Please refer to the corresponding Moodle course.

Moodle Course(s)

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