Courses Offered

COMP2501 Introduction to data science and engineering

COMP2501 Introduction to data science and engineering

2022-23
Instructor(s):Ting HF
(Class A) No. of credit(s):6
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
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 aPLO bPLO cPLO dPLO ePLO fPLO gPLO hPLO iPLO j
CLO 1TTT
CLO 2TT
CLO 3TT
CLO 4TT

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 acquisition1
Data pre-processing1
Data manipulation1
Feature engineering1
Data Analysis Mapped to CLOs
Exploratory data analysis2
Statistical Inference and Regression Models2
Machine Learning2
Implementation Mapped to CLOs
Python for data science3
Visualization and Communication Mapped to CLOs
Data visualization tools4

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

Teaching Plan

Please refer to the corresponding Moodle course.

Moodle Course(s)

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