Courses Offered

COMP2501 Introduction to data science and engineering

2024-25

Instructor(s):

Ting HF

(Class A)

No. of credit(s):

Luo Ruibang

(Class B)

Recommended Learning Hours:

Lecture:	27.0
Tutorial:	12.0

Pre-requisite(s):

COMP1117 or ENGG1330

Co-requisite(s):

Mutually exclusive with:

STAT1005 or STAT1015 or STAT1018

Remarks:

Course Learning Outcomes

1.	[Data Preparation and Manipulation] Able to demonstrate practical knowledge in data preparation and data manipulation.
2.	[Data Analysis] Able to use appropriate modelling and analysis techniques for data science problems.
3.	[Implementation] Able to implement practical solutions for data science problems.
4.	[Visualization and Communication] Able to communicate data analysis results effectively.

Mapping from Course Learning Outcomes to Programme Learning Outcomes
	PLO a	PLO b	PLO c	PLO d	PLO g	PLO j
CLO 1	T	T				T
CLO 2			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:
The course introduces basic concepts and methodology of data science. The goal of this course is to provide students with an overview and practical experience of the entire data analysis process. Topics include: data source and data acquisition, data preparation and manipulation, exploratory data analysis, statistical and predictive analysis, data visualization and communication.

Detailed Description:

Data Preparation and Manipulation	Mapped to CLOs
Data source and data acquisition	1
Data pre-processing	1
Data manipulation	1
Feature engineering	1
Data Analysis	Mapped to CLOs
Exploratory data analysis	2
Statistical Inference and Regression Models	2
Machine Learning	2
Implementation	Mapped to CLOs
Python for data science	3
Visualization and Communication	Mapped to CLOs
Data visualization tools	4

Assessment:
Continuous Assessment: 50%
Written Examination: 50%

Teaching Plan

Please refer to the corresponding Moodle course.

Moodle Course(s)

Courses Offered

COMP2501 Introduction to data science and engineering

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