Big Data Algorithms for Engineering Course
This course equips you with big data algorithms for real-time analytics. Dive into streaming architectures, scalable metrics like HLL and Top-K, event modelling for video data, and strategies for cost-effective, reliable pipelines. Perfect for powering video platforms and large-scale systems with precise, actionable insights to drive engineering success.

from 4 to 360h 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 fast analytics. Hands-on practice with Top-K, HyperLogLog, sessionization, and error metrics, plus tips to optimise cost, reliability, and performance using real-world pseudocode and patterns.
Elevify advantages
Develop skills
- Design efficient streaming data pipelines for low-latency, reliable workflows.
- Implement scalable metrics using HLL, Top-K, and session windows for live KPIs.
- Model video events with analytics-focused schemas that ensure quality and evolution.
- Optimise big data expenses by 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 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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