Learn the fundamental algorithms and theories used for understanding large-scale graphs and knowledge graphs.
Many real-world datasets come in the form of graphs. These datasets include social networks, biological networks, knowledge graphs, the World Wide Web, and many more. Having a comprehensive understanding of these networks is essential to truly understand many important applications.
This course introduces the fundamental concepts and tools used in modeling large-scale graphs and knowledge graphs. You will learn a spectrum of techniques used to build applications that use graphs and knowledge graphs. These techniques range from traditional data analysis and mining methods to the emerging deep learning and embedding approaches.Release schedule:
This course is of rolling release model, there are 5 modules in this course, module 1 is released when the course is live on Jan 16, 2019, other modules will be released according to the following schedule:
- Jan 23, 2019: Module 2 and Module 3
- Jan 30, 2019: Module 4 and Module 5
What will you learn
- Explore large-scale networks with different structures and properties;
- Learn graph representations using advanced deep learning and embedding techniques;
- Utilize NLP fundamentals to build knowledge graphs;
- Use knowledge graphs in modern search applications;
- Model knowledge graphs using embedding methods.