Computer Scientist Course
Dive into advanced graph algorithms for distance queries and k-closest searches on massive networks. Explore exact BFS baselines, approximate methods like embeddings, sketches, and PageRank, while balancing complexity, scalability, and performance. Gain skills to design experiments, optimise systems, and apply solutions in real-world tech environments, preparing you for high-impact computer science challenges.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This course provides a thorough, practical guide to mastering graph distance queries and k-closest searches on large networks. Learners will cover problem definitions, exact BFS methods, approximate techniques using embeddings, sketches, and PageRank, along with complexity analysis, scalability issues, and experimental design. By the end, participants will confidently select, implement, and assess efficient solutions.
Elevify advantages
Develop skills
- Design graph distance metrics: model, compare, and choose for k-closest queries.
- Implement exact BFS searches: build scalable k-closest algorithms efficiently.
- Create approximate indexes: develop sketches, embeddings, and APPR for quick searches.
- Conduct large-graph experiments: plan, execute, and analyse performance tests.
- Optimise graph systems: adjust memory, parallelism, and layouts for big data.
Suggested summary
Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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