COURSE INFO
VECTOR[3-0-0:3]
DESCRIPTIONWith more and more data available, data mining and knowledge discovery has become a major field of research and applications in data science. Aimed at extracting useful and interesting knowledge from large data repositories such as databases, scientific data, social media and the Web, data mining and knowledge discovery integrates techniques from the fields of database, statistics and AI.

DSAA 5002 - Data Mining and Knowledge Discovery in Data Science (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L01 (6031) Mo 03:00PM - 05:50PMRm 101, W1LI, Jia10081190 
COURSE INFO
VECTOR[3-0-0:3]
DESCRIPTIONIn this course, theories, models, algorithms of deep learning and their application to data science will be introduced. The basics of machine learning will be reviewed at first, then some classical deep learning models will be discussed, including AlexNet, LeNet, CNN, RNN, LSTM, and Bert. In addition, some advanced deep learning techniques will also be studied, such as reinforcement learning, transfer learning and graph neural networks. Finally, end-to-end solutions to apply these techniques in data science applications will be discussed, including data preparation, data enhancement, data sampling and optimizing training and inference processes.

DSAA 5009 - Deep Learning in Data Science (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L01 (6032) Tu 01:30PM - 04:20PMLecture Hall CWANG, Wenjia12096240 
COURSE INFO
VECTOR[3-0-0:3]
DESCRIPTIONIn this course, the concepts and implementation schemes in advanced database management systems for data science applications will be introduced, such as disk and memory management, advanced access methods, implementation of relational operators, query processing and optimization, transactions and concurrency control. It also introduces emerging database related techniques for data science.

DSAA 5012 - Advanced Database Management for Data Science (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L01 (6033) 22-JAN-2024 - 14-MAR-2024
Fr 01:30PM - 04:20PM		Rm 101, E1LI, Lei9024660 
15-MAR-2024 - 10-MAY-2024
Fr 01:30PM - 04:20PM		Rm 202, E3LI, Lei
COURSE INFO
VECTOR[3-0-0:3]
DESCRIPTIONIn this course, advanced algorithms for data science will be introduced. It covers most of the classical advanced topics in algorithm design, as well as some recent algorithmic developments, in particular algorithms for data science and analytics.

DSAA 5013 - Advanced Machine Learning (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L01 (6034) We 01:30PM - 04:20PMRm 101, W1CHU, Xiaowen10053470 
COURSE INFO
VECTOR[3-0-0:3]
DESCRIPTIONThis course introduces basic concepts and technologies of blockchain, such as the hash function and digital signature, as well as data analysis and privacy protection over blockchain applications. The students will learn the consensus protocols and algorithms, the incentives and politics of the block chain community, the mechanics of Bitcoin and Bitcoin mining, data analysis techniques over blockchain and user/transaction privacy protection.

DSAA 5022 - Data Analysis and Privacy Protection in Blockchain (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L01 (6035) Tu 09:00AM - 11:50AMRm 201, E1TANG, Jing307230 
COURSE INFO
VECTOR[3-0-0:3]
DESCRIPTIONTo serve large-scale and practical AI models, having good algorithms is just a start. In this course, we cover various ML ops techniques to deploy and retrain AI models for practice. Many guest speakers from the industry will share their experiences and challenges, and as a term project, we will build a practical AI system.

DSAA 6000E - Model to Production: ML Ops for Real Industry (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L01 (6037) Fr 09:00AM - 11:50AMRm 202, W4KIM, Sung Hun3015150 
COURSE INFO
VECTOR[3-0-0:3]
DESCRIPTIONRelational Database Management Systems (RDBMS) are the main systems for businesses to process transactions and store data. In real-world scenarios, organizations often maintain multiple relational databases to serve different business applications and meet different needs. Data warehouses integrated data from multiple RDBMS are built to facilitate planning and decision making in businesses. Online analytical processing (OLAP) is a technology that uses a data warehouse for answering aggregation queries often used in planning. While data warehouses hold important information about a business, the success of a business quite often depends on advanced planning and development of strategies based on customer behavior. This course introduces the key mechanisms in data warehousing and OLAP. It discusses the logical and physical design of data warehouses including data schema, data marts, and data cube technologies. In practical aspects, students study the use of data warehouses through a study of the OLAP technology, and know the common data warehousing software tools to solve real-world problems.

DSAA 6000H - Data Warehousing (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L01 (6038) Mo 09:00AM - 11:50AMRm 201, E1WEN, Zeyi308220 
COURSE INFO
VECTOR[3-0-0:3]
DESCRIPTIONThis graduate-level course is designed for multi-discipline students to learn and apply industrial analytics techniques for problem-solving and process improvement in various industries. The course will emphasize the Define, Measure, Analyze, Improve, and Control (DMAIC) methodology, along with other data-driven techniques for process improvement and problem-solving. Students will gain hands-on experience through case studies, assignments, and a term project. Prerequisites: Basic knowledge of statistics, data analysis, and engineering principles.

DSAA 6000L - Industrial Analytics for Problem Solving and Process Improvement (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L01 (6173) 22-JAN-2024 - 14-MAR-2024
Th 09:00AM - 11:50AM		Rm 102, E1TSUNG, Fu-Gee305250 
15-MAR-2024 - 10-MAY-2024
Th 09:00AM - 11:50AM		Rm 105, E3TSUNG, Fu-Gee
COURSE INFO
VECTOR[1 credit]
DESCRIPTIONThis course offers students opportunities to learn the possible industry topics and supervisors that they will work with during their internship. The goals are: (a) understand (i) problems in industry, (ii) existing data-sets, (iii) AI models, (iv) service scenario and KPI, (v) challenges; (b) propose industrial projects based on the understanding; and (c) matching for their industrial projects. This course is only available for MSc(DCAI) students. Graded P or F.

DSAA 6010 - Industry Round Table (1 unit)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L01 (6164) 22-JAN-2024 - 14-MAR-2024
Fr 04:30PM - 06:20PM		Rm 101, E1CHEN, Lei
CHU, Xiaowen
KIM, Sung Hun
TANG, Nan
WANG, Wei		605370
Class of March 15th will be delivered in E1-134.
 
15-MAR-2024 - 15-MAR-2024
Fr 04:30PM - 06:20PM		TBACHEN, Lei
CHU, Xiaowen
KIM, Sung Hun
TANG, Nan
WANG, Wei
18-MAR-2024 - 10-MAY-2024
Fr 04:30PM - 06:20PM		Rm 101, W1CHEN, Lei
CHU, Xiaowen
KIM, Sung Hun
TANG, Nan
WANG, Wei
COURSE INFO
VECTOR[1-3 credit(s)]
DESCRIPTIONIn this course, an independent research project will be carried out under the supervision of a faculty member.

DSAA 6018A - Independent Study (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
R01 (6185) TBATBATBA201190
Instructor Consent Required
 
COURSE INFO
VECTOR[1-0-0:1]
DESCRIPTIONIn this course, students are required to attend at least 6 seminars offered by the program. The program will offer at least 10 seminars related to the state-of-the-art research on data science and analytics in each term. These seminars will help students to broaden the horizons of their knowledge on data science and analytics. Graded P or F.

DSAA 6102 - Data Science and Analytics Program Seminar II (1 unit)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L01 (6036) We 10:00AM - 10:50AMRm 101, W1TANG, Nan120102180 
COURSE INFO
VECTOR[6 credits]
DESCRIPTIONIn this course, the student will work on a practical project. The independent project is related to real problems existing in data science and AI application domains. The student needs to conduct literature survey, method comparison, solution selection and implementation, experimental study and write the final report. The course will train students skills on proposing end-to-end solution for a realapplications problem. This course is only available for MSc(DCAI) students. Graded P or F.

DSAA 6800 - Independent Project (6 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
R01 (6321) 22-JAN-2024 - 14-MAR-2024
Mo 09:00AM - 12:50PM		Rm 122, E1CHEN, Lei605190 
22-JAN-2024 - 08-APR-2024
Tu 04:30PM - 06:20PM		Rm 228, E2CHEN, Lei
15-MAR-2024 - 10-MAY-2024
Mo 09:00AM - 12:50PM		Rm 101, W1CHEN, Lei
09-APR-2024 - 10-MAY-2024
Tu 04:30PM - 06:20PM		Rm 101, W1CHEN, Lei
COURSE INFO
DESCRIPTIONMaster's thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned.

DSAA 6990 - MPhil Thesis Research (0 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
R01 (6039) TBATBATBA999289710 
COURSE INFO
DESCRIPTIONOriginal and independent doctoral thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned.

DSAA 7990 - Doctoral Thesis Research (0 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
R01 (6040) TBATBATBA99979920