Big Data Algorithms for Engineering Course
Master the algorithms that power modern data engineering at scale. This course takes you from foundational big data concepts through distributed machine learning, graph processing, and real-time stream analytics. You will gain the technical depth to design, optimize, and deploy production-grade big data systems with confidence.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
You will build a complete understanding of big data algorithms, starting with the five V's and computational complexity at scale. You will implement MapReduce patterns, probabilistic sketching techniques, and streaming algorithms designed for unbounded data. The course covers distributed machine learning strategies including federated learning and gradient descent parallelization. You will also learn graph processing at billion-node scale, advanced indexing structures, and cost-based query optimization. By the end, you will have a practical framework for selecting the right algorithm for any large-scale engineering challenge.
Elevify advantages
Develop skills
- MapReduce Pipeline Design: implement and optimize batch processing algorithms across billions of records.
- Stream Processing Architecture: build real-time event pipelines with millisecond latency and fault tolerance.
- Probabilistic Algorithm Tuning: select and configure sketching and sampling methods for memory-efficient analytics.
- Distributed ML Parallelization: deploy data-parallel and model-parallel training pipelines on large-scale datasets.
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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