Big Data Algorithms for Engineering Course
Gain mastery in big data algorithms for real-time analytics. Explore streaming architectures, scalable metrics like HyperLogLog and Top-K, event schema design, and strategies for cost-effective, dependable pipelines to drive video platforms and large-scale systems with precise insights. This hands-on course uses practical pseudocode to boost performance and reliability.

flexible workload of 4 to 360h
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, plus error metrics. Optimise for cost, reliability, and speed using real-world pseudocode 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, and monitoring.
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 workloadWhat our students say
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Giulio CarloDigital Marketing Student
I like how the lessons are straight to the point and how I can change chapters and skip content I don't need.

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The platform is fast, simple to use. The diversity of content and complementary videos help a lot with learning.

André FelipePrompt Engineering Student
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