SDSC5002 Course Information

#sdsc5002 #course information

English / 中文

Course Overview

Course Code: SDSC5002C61

Course Name: Exploratory Data Analysis and Visualization

Semester: 2025/26 Fall Semester

Instructor: Prof. Lijia WANG

Email: lijiwang@cityu.edu.hk

Office: LAU-16-272

Lecture Time: Not specified (check Canvas for updates)

Consultation Hours: Not specified

Teaching Mode: Face-to-face

Teaching Assistants:

  • Ms. Minghe LI (mingheli2-c@my.cityu.edu.hk) for Tableau

  • Mr. Yanxin YIN (wl.z@cityu.edu.hk) for Python

Assessment Method

Component Weight Details
Group Project 40% Group work (4-8 members). Presentation in weeks 11-13.
Individual Coursework 25% Includes quizzes and assignments. On-time quiz submission: 2 points, late: 1 point. Assignments graded, full grade 10 points.
Midterm Exam 35% Week 10. Closed book; allowed one A4 note sheet.

Schedule and Teaching

Week Date Activity Content Deadline
1 Sep 6 Lecture Key concepts of exploratory data analysis and data visualization
2 Sep 13 Lecture Data analytics and visualization for machine learning
Tutorial 1 Python and Tableau introduction
3 Sep 20 Lecture High-dimensional data visualization
Tutorial 2 Data exploration practical (e.g., Iris dataset)
4 Sep 27 Lecture Visualization for machine learning, Linear regression
Tutorial 3 Cross-validation and linear regression practice
5 Oct 4 National Day No class Group formation deadline
6 Oct 11 Lecture Model selection, regularization, Classification methods
Tutorial 4 Subset selection, shrinkage methods, PCR, PLS
7 Oct 18 Lecture Classification methods, Midterm exam Q&A
Tutorial 5 Classification methods practice
8 Oct 25 Lecture High-dimensional data techniques
9 Nov 1 Chung Yeung Festival No class Project proposal submission
10 Nov 8 Midterm Exam Midterm test (closed book, one A4 note allowed)
11 Nov 15 Lecture Visualization of networks Start of project presentations
12 Nov 22 Project presentations
13 Nov 29 Project presentations, Course summary Final project report submission

Project Requirements (20% of total grade)

Key Deadlines:

  1. Group Formation

    • Deadline: Before Week 10 (by Nov 1, 2025)
    • Form teams of 4-8 members. Submit team details via Canvas.

  2. Project Proposal

    • Deadline: Week 9 (Nov 1, 2025)
    • Format: ≥0.5-page PDF proposal. Submit to Canvas → Assignment: Project Proposal.

  3. Final Submission

    • Deadline: Week 13 (Nov 29, 2025)
    • Deliverables:
      • Poster: A0-size slide (1189×841 mm) as PDF.
      • Main Report: ≤6-page PDF (cover, member roles, background, data, methods, results, conclusion).
      • Appendix: Source code PDF.

Project Rules:

  • Topic: Self-selected, must apply statistical/machine learning methods to solve real-world problems.

  • Data: Must use Hong Kong Government Open Data.

  • Originality: Original work for this course; no reuse from other courses or papers.

  • Grading: Focus on scientific value; plagiarism prohibited.