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HKU Summer Institute
Data Science for Beginners: Theory, Algorithms and Applications"

Programme Code: IDSS2301

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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

  1. Understanding of the mathematical foundations of data science
  2. Ability to construct mathematical models for real-world data analytic problems
  3. Ability to process and analyze real-world, large-scale data sets
  4. Ability to implement data science related algorithms
  5. Appreciation of the broad and powerful applicability of data science

Key Topics:

  1. Optimization: basic theory and modeling
  2. Optimization: algorithms
  3. Bayesian statistics
  4. Network theory
  5. Basics of machine learning
  6. Basics of neural network

Teaching Methods: Lectures, Programming Tutorials

Programme Schedule

Mondays to Fridays (09:30-12:30; 14:00-17:00)

Week 1July 10
(Monday)
July 11
(Tuesday)
July 12
(Wednesday)
July 13
(Thursday)
July 14
(Friday)
Morning Session
(09:30-12:30)
Opening CeremonyNearest NeighboursNaive Bayes ClassifiersInteger ProgrammingNonlinear Programming II
Afternoon Session
(14:00-17:00)
Performance Evaluation: Variance-Bias Trade-offSocial Activities (Optional)Linear ProgrammingNonlinear Programming INeural network and stochastic methods I
Week 2July 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 IIBayesian Sampling and EstimationFoundations of Network ScienceStatistical Inference for Network Data Part II 
Afternoon Session
(14:00-17:00)
Foundations of Bayesian StatisticsSocial Activities (Optional)Statistical Inference for Network Data Part IClosing 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

10% – Partnership Discount / Referral Discount / HKU Family Discount (Staff, Students, and Alumni)
20% – HKUSI Alumni Discount
 
* All discounts are NOT in conjunction with any other discounts.