HKU Summer Institute Data Science for Beginners: Theory, Algorithms and Applications"
Programme Code: IDSS2301
Apply Now!Programme Description
Areas of interest: Machine Learning . Optimization . Statistics . Neural Network . Network Science
Data science has grown to become a large, interdisciplinary subject and an integral part of the society, with applications found across a wide range of domains. This summer course offers a friendly introduction to a number of important topics in data science, focusing on the mathematical and algorithmic foundations. Applications of data science in various scientific, engineering and business domains will also be presented.
Learning Outcomes
- Understanding of the mathematical foundations of data science
- Ability to construct mathematical models for real-world data analytic problems
- Ability to process and analyze real-world, large-scale data sets
- Ability to implement data science related algorithms
- Appreciation of the broad and powerful applicability of data science
Key Topics:
- Optimization: basic theory and modeling
- Optimization: algorithms
- Bayesian statistics
- Network theory
- Basics of machine learning
- Basics of neural network
Teaching Methods: Lectures, Programming Tutorials
Programme Schedule
Mondays to Fridays (09:30-12:30; 14:00-17:00)
| Week 1 | July 10 (Monday) | July 11 (Tuesday) | July 12 (Wednesday) | July 13 (Thursday) | July 14 (Friday) |
|---|---|---|---|---|---|
| Morning Session (09:30-12:30) | Opening Ceremony | Nearest Neighbours | Naive Bayes Classifiers | Integer Programming | Nonlinear Programming II |
| Afternoon Session (14:00-17:00) | Performance Evaluation: Variance-Bias Trade-off | Social Activities (Optional) | Linear Programming | Nonlinear Programming I | Neural network and stochastic methods I |
| Week 2 | July 17 (Monday) | July 18 (Tuesday) | July 19 (Wednesday) | July 20 (Thursday) | End of Programme |
|---|---|---|---|---|---|
| Morning Session (09:30-12:30) | Neural network and stochastic methods II | Bayesian Sampling and Estimation | Foundations of Network Science | Statistical Inference for Network Data Part II | |
| Afternoon Session (14:00-17:00) | Foundations of Bayesian Statistics | Social Activities (Optional) | Statistical Inference for Network Data Part I | Closing Ceremony |
The programme content is subject to change without prior notice.
Assessment
Coursework, Presentations
Programme Instructor(s)
- Prof. Yi MA (guest lecturer)
- Dr. Sebastian MOREL BALBI
- Dr. Man Chung YUE
- Dr. Yue XIE
Eligibility
- A student who is currently studying for a bachelor/master degree.
- A candidate who meets the undergraduate admission requirements of HKU (or other recognised Universities) by possessing adequate secondary school or sub-degree qualification.
Programme Fee
HKD 12,800
20% – HKUSI Alumni Discount