Courses Offered

COMP2501 Introduction to data science and engineering

2021-22

Instructor(s):

Ting HF

(Class A)

No. of credit(s):

Recommended Learning Hours:

Lecture:	27.0
Tutorial:	12.0

Pre-requisite(s):

COMP1117 or ENGG1330

Co-requisite(s):

Mutually exclusive with:

STAT1005 or STAT1015

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.

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

Syllabus

Calendar Entry:

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)