EE4146Data Engineering and Machine Learning

这门课学什么

课程概述与目标

This course aim is to introduce the concept, techniques and fundamental background to informatics and learning systems.

教学内容（Keyword Syllabus）

Introduction to Data Engineering Understand data engineering methodologies, learning systems and its analysis; formulate an IT/business/engineering problem from the perspective of learning systems; understand fundamental concepts in data engineering and classification; recognize issues in practical data engineering and IT problems. Emerging Machine Learning Technology Introduction to Machine Learning Technology: Statistical methods such as Discriminant Analysis, and Principal Component Analysis; Supervised learning such as Naïve Bayes classifier, K Nearest Neighbour, and neural networks; Unsupervised learning approaches such as Self-Organizing Map, and Clustering; High Dimensionality Reduction such as linear discriminant analysis (LDA), manifold learning, and feature selection methods; Diagnostic Analysis, and Practical Case Study.

校方 PDF 第 4 页 · Keyword Syllabus

预期学习成果

查看学习成果表

CILO	预期学习成果	比重	DEC
1	Describe the current learning systems and methodologies used in engineering, IT and data industries	—	DEC-A1, DEC-A2
2	Describe the use of supervised and unsupervised learning methods for engineering, IT and data engineering problems	—	DEC-A1, DEC-A2
3	Analyze practical data engineering and machine learning problems using supervised or unsupervised learning methods	—	DEC-A1, DEC-A2

校方 PDF 第 2 页 · Course Intended Learning Outcomes (CILOs)

我能不能修这门课

先修、建议先备和并修要求分别查看；等同及互斥条件也会影响选课。and 表示同时满足，or 表示备选；组合条件按下方原文分组阅读。

先修条件

(MA3001 Differential Equations or EE3121 Differential Equations for Electrical Engineering) or EE3001 Foundations of Data Engineering or (MA3160 Probability and Stochastic Processes or EE3331 Probability Models in Information Engineering)

建议先备知识

EE3211 Modelling Techniques

并修要求

该版官方课纲未列明该项。

其他修读要求

该版官方课纲未列明该项。

等同课程及条件

无（校方注明 Nil）

互斥课程及条件

无（校方注明 Nil）

怎么考，怎样才算通过

考核方式

Continuous assessment: 50%; Examination: 50%; Examination duration: 2 hours

各项考核占多少分

考核项目	比重	生成式 AI 使用	备注与限制
TestsCILO 1, 2, 3	35%	否（No）	-
AssignmentsCILO 1, 2, 3	15%	是（Yes）	-

校方 PDF 第 3 页 · Assessment Tasks / Activities (ATs)

查看校方原始考核表与使用要求

Tests (min.: 2) | CILO No. 1,2,3 | 35% | - | No
#Assignments (min.: 3) | CILO No. 1,2,3 | 15% | - | Yes

通过条件

Remarks: To pass the course, students are required to achieve at least 30% in course work and 30% in the examination. # may include homework, tutorial exercise, project/mini-project, presentation.

目录页标明这些考核比例为参考值；详细考核安排以课程课纲为准。