Big Data Algorithms for Engineering Course
Dive into big data algorithms for real-time analytics in this focused course. Explore streaming architectures, scalable metrics like HyperLogLog and Top-K, event schema design for video data, and techniques to optimise costs while ensuring reliable, high-performance pipelines for large-scale systems delivering precise insights.

4 to 360 hours flexible workload
valid certificate in your country
What will I learn?
Gain expertise in essential big data algorithms and streaming systems through this practical course. Design event schemas, create scalable data ingestion pipelines, and select optimal processing engines for real-time analytics. Hands-on practice with Top-K, HyperLogLog, sessionization, and error metrics, plus optimisation strategies for cost, reliability, and performance using practical pseudocode and patterns.
Elevify advantages
Develop skills
- Design efficient streaming data pipelines for low-latency, reliable workflows.
- Implement scalable metrics using HyperLogLog, Top-K, and session windows for live KPIs.
- Model video events with analytics-focused schemas that support evolution and quality control.
- Optimise big data expenses through tuning storage, compute, partitioning, and compaction.
- Strengthen pipelines with fault tolerance, testing, monitoring, and anomaly detection.
Suggested summary
Before starting, you can change the chapters and the 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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