IERG4300 Web-scale Information Analytics
2025/5/11小于 1 分钟
Course Basic Info
Course Website: https://mobitec.ie.cuhk.edu.hk/ierg4300Spring2023/
Prerequisites: Solid knowledge in Probability, Statistics, Linear Algebra and computer programming skills
Core Course Content
This course focuses on data-intensive analytics and automated processing of massive structured/unstructured data, centering on MapReduce and parallel computing paradigms for web-scale data processing. Key topics include:
- MapReduce computational model, system architecture and practical implementation
- Frequent Item-sets & Association Rules mining, similar items search in high-dimensional data
- Dimensionality Reduction techniques, Clustering algorithms and Recommendation systems
- Massive Graph analysis and its applications on the World Wide Web
- Large-scale supervised machine learning
- Data Streams processing & mining, and applications in large-scale network/online-activity monitoring
Outcomes
Systematic mastered the design of parallel algorithms for web-scale data processing, and gained practical experience in MapReduce-based massive data analysis, laying a solid foundation for subsequent big data and distributed computing related practice.