EE1004信息系统与数据分析基础

这门课学什么

课程概述与目标

This course is designed to introduce the students to concepts, impacts, and basic principles of data and information systems. Applied examples will be introduced, analysed, solved. The laboratories of this course will cover introductory probability problems and statistics of real-life data, geometric transformation, and applications of eigenvalues and eigenvectors to data analysis.

教学内容（Keyword Syllabus）

Introduction to Data and Information Systems Numerical and non-numerical data; Signals and images; Graphs: nodes, edges, adjacency matrix. Basic Computational Engineering and Linear Algebra Introduction to computational engineering and modeling of physical systems; Vectors: inner and outer products; Matrices: matrix multiplications, determinants, inverse of a matrix; System of linear equations; Eigenvector and Eigenvalues; Application to geometric image transformations. Information System and Data Statistics and Probability Introduction to modeling of information and engineering systems using basic statistics and probability; Summarizing data sets: measures of center and measures of variation; Sample space and events, basic laws of probability, conditional probability; Application to engineering problems. Engineering Data Modeling and Random Variables Introduction to Information and engineering systems data modeling; The ideas of summation and integration; probability mass function, probability density function, common random variables (e.g., binomial, Poisson, Gaussian), expectation and variance; Joint distribution functions, independent random variables, covariance, and correlation; Application to data modeling. Basic Engineering Statistical Methods Sampling distributions and basic point estimates, confidence intervals for a population mean; Hypothesis testing: the null and the alternative hypotheses, two types of errors, p values; Application to engineering data analysis.

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	Explain mathematical concepts on topics of linear algebra, including vectors, matrices, linear equations, etc in engineering applications	—	DEC-A1, DEC-A2
2	Describe basic statistical methods in engineering applications	—	DEC-A1, DEC-A2
3	Describe engineering data modeling and random variables	—	DEC-A1, DEC-A2
4	Analyze data using basic statistics and probability theories	—	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

无（校方注明 Nil）

建议先备知识

无（校方注明 Nil）

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
Tests and short testsCILO 1, 2, 3, 4	30%	否（No）	-
Assignments and Lab AssignmentsCILO 1, 2, 3, 4	20%	是（Yes）	-

校方 PDF 第 2–3 页 · Assessment Tasks / Activities (ATs)

查看校方原始考核表与使用要求

Assessment Tasks / Activities (ATs)
                      ATs                   CILO No.                Weighting (%)             Remarks ("-" for     Allow Use of
                                                                                              nil entry)           GenAI?
1                     Tests (min. 2) and    1, 2, 3, 4              30                        -                    No
                      short tests

3      EE1004: Foundations of Information Systems and Data Analysis




2                       # Assignments and 1, 2, 3, 4                  20         -                   Yes
                        Lab Assignments
                        (total: 5)

通过条件

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