Big Data Algorithms for Engineering Course
Gain expertise in big data algorithms for real-time analytics. Explore streaming architectures, scalable metrics like HyperLogLog and Top-K, event schema design for video platforms, and strategies to optimise costs, boost reliability, and enhance performance in large-scale systems for precise insights.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Master essential big data algorithms and streaming setups in this practical course. Design event schemas, create scalable data ingestion pipelines, select optimal processing engines for quick analytics, and work with Top-K, HyperLogLog, sessionization, and error metrics. Optimise for cost, reliability, and speed using real-world examples and patterns.
Elevify advantages
Develop skills
- Design streaming data pipelines for low-latency, reliable workflows.
- Implement scalable metrics using HLL, Top-K, and session windows.
- Model video events with analytics-focused schemas and quality controls.
- Optimise big data costs through storage, compute, and partitioning tuning.
- Strengthen pipelines with fault tolerance, testing, monitoring, and alerts.
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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