SDST4609 Big data analytics (6 credits) Academic Year 2025
Offering Department SCDS (Department of Statistics and Actuarial Science) Quota 50
Course Co-ordinator Prof M M Y Zhang, SCDS (Department of Statistics and Actuarial Science) < mzhang18@hku.hk >
Teachers Involved (Prof M M Y Zhang,Statistics & Actuarial Science)
Course Objectives In the past decade, huge volume of data with highly complicated structure has appeared in every aspect, such as social web logs, e-mails, video, speech recordings, photographs, tweets and others. The efficient extraction of valuable information from these data sources becomes a challenging task. This course focuses on the practical knowledge and skills of some advanced analytics and statistical modeling for solving big data problems.
Course Contents & Topics Recommender systems, Link analysis, Social network analysis, Text analytics, Sentiment analysis, Topic modeling, Deep Learning, and Reinforcement learning
Course Learning Outcomes
On successful completion of this course, students should be able to:

CLO 1 understand and apply a wide range of data analytic techniques, and recognize their characteristics, strengths and weaknesses
CLO 2 obtain hands-on experience of computer software for data analytics
CLO 3 identify and use appropriate data analytic techniques for data extraction, taking into account both the structure of the data and the goals of the user of the discovered knowledge
CLO 4 evaluate the quality of discovered knowledge, taking into account the requirements of the data analytic task being performed and the goals of the user
Pre-requisites
(and Co-requisites and
Impermissible combinations)		 Pass in SDST3612 or SDST4904
Only for students admitted in 2025 and thereafter.
Course Status with Related Major/Minor /Professional Core 2U000C00 Course not offered under any Major/Minor/Professional core
2024 Major in Decision Analytics ( Core/Compulsory )
2023 Major in Decision Analytics ( Core/Compulsory )
2022 Major in Decision Analytics ( Core/Compulsory )
2021 Major in Decision Analytics ( Core/Compulsory )
Course to PLO Mapping 2024 Major in Decision Analytics < PLO 1,2,3,4,5,6 >
2023 Major in Decision Analytics < PLO 1,2,3,4,5,6 >
2022 Major in Decision Analytics < PLO 1,2,3,4,5,6 >
2021 Major in Decision Analytics < PLO 1,2,3,4,5,6 >
Offer in 2025 - 2026 Y        2nd sem    Examination No Exam     
Offer in 2026 - 2027 Y
Course Grade A+ to F
Grade Descriptors
A Demonstrate thorough mastery at an advanced level of extensive knowledge and skills required for attaining all the course learning outcomes. Show strong analytical and critical abilities and logical thinking, with evidence of original thought, and ability to apply knowledge to a wide range of complex, familiar and unfamiliar situations. Apply highly effective organizational and presentational skills.
B Demonstrate substantial command of a broad range of knowledge and skills required for attaining at least most of the course learning outcomes. Show evidence of analytical and critical abilities and logical thinking, and ability to apply knowledge to familiar and some unfamiliar situations. Apply effective organizational and presentational skills.
C Demonstrate general but incomplete command of knowledge and skills required for attaining most of the course learning outcomes. Show evidence of some analytical and critical abilities and logical thinking, and ability to apply knowledge to most familiar situations. Apply moderately effective organizational and presentational skills.
D Demonstrate partial but limited command of knowledge and skills required for attaining some of the course learning outcomes. Show evidence of some coherent and logical thinking, but with limited analytical and critical abilities. Show limited ability to apply knowledge to solve problems. Apply limited or barely effective organizational and presentational skills.
Fail Demonstrate little or no evidence of command of knowledge and skills required for attaining the course learning outcomes. Lack of analytical and critical abilities, logical and coherent thinking. Show very little or no ability to apply knowledge to solve problems. Organization and presentational skills are minimally effective or ineffective.
Communication-intensive Course N
Course Type Lecture-based course
Course Teaching
& Learning Activities
Activities Details No. of Hours
Lectures 36.0
Tutorials 12.0
Reading / Self study 100.0
Assessment Methods
and Weighting
Methods Details Weighting in final
course grade (%)		 Assessment Methods
to CLO Mapping
Assignments 30.0 1,2,3,4
Project reports May include project proposal and presentation 30.0 1,2,3,4
Test 40.0 3,4
Required/recommended reading
and online materials		 Geron, A. (2019). Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems. 2nd edition, O'Reilly Media.
Aggarwal, C.C. (2016). Recommender Systems: The Textbook. Springer, New York.
Sarkar, D. (2016). Text Analytics with Python. Apress.
Chollet, F. (2018). Deep Learning with Python. MANNING.
Course Website http://moodle.hku.hk
Additional Course Information NIL