VECTOR | [3-0-0:3] |
---|---|
PRE-REQUISITE | IPEN 5110 |
DESCRIPTION | This course focuses on the theoretical and analytical perspective of public management and institutions. It introduces students to key concepts in the discipline of public management and institutional analysis. The course begins with a review of the evolution of thinking in this field. In the following sessions, students will be extensively exposed to theoretical frameworks. The course aims to equip students with theories that help students in building up their capacity toward academic research. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
---|---|---|---|---|---|---|---|---|
L01 (6087) | Fr 09:00AM - 11:50AM | Rm 201, E4 | XU, Kewei | 15 | 5 | 10 | 0 |
VECTOR | [3-0-0:3] |
---|---|
DESCRIPTION | This course serves as an applied introduction to machine learning methods for text analysis. Several approaches on text data management and analysis will be covered in this course including basic natural language processing techniques, document representation, text categorization and clustering, document summarization, sentiment analysis, social network and social media analysis, probabilistic topic models and text visualization. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
---|---|---|---|---|---|---|---|---|
L01 (6088) | We 09:00AM - 11:50AM | Rm 202, W4 | XU, Kewei | 30 | 19 | 11 | 0 |
VECTOR | [2-0-0:2] |
---|---|
PREVIOUS CODE | IIMP 6010 |
DESCRIPTION | This course focuses on using various approaches to perform quantitative analysis through real-world examples. Students will learn how to use different tools in an interdisciplinary project and how to acquire new skills on their own. The course offers different modules that are multidisciplinary/multifunctional and generally applicable to a wide class of problems. May be graded PP. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
---|---|---|---|---|---|---|---|---|
L01 (6136) | TBA | TBA | CAI, Yi CUI, Ying GAN, Zecheng LI, Lei MA, Jun TAN, Chee Keong XIONG, Hui XU, Kewei ZHANG, Zhuoni | 350 | 351 | 0 | 0 |