Large Scale Machine Learning Course
This course covers the end-to-end process of building and deploying large-scale machine learning recommendation systems, focusing on scalability, efficiency, and operational best practices.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
The Large Scale Machine Learning Course teaches you how to design, train, and serve high-performance recommendation models from start to finish. You will learn scalable data ingestion, streaming pipelines, feature engineering, and low-latency serving using ANN systems. Build reliable, cost-efficient ML platforms with monitoring, observability, governance, security, and robust evaluation to confidently operate models at tens-of-millions scale.
Elevify advantages
Develop skills
- Design large-scale recommenders: two-tower, ANN and matrix factorization.
- Train ML models at scale: negative sampling, tuned loss and hyperparameters.
- Build low-latency ML serving: feature stores, ANN retrieval and A/B tests.
- Engineer batch and streaming features with Spark, Kafka and Parquet.
- Operationalize ML: monitoring, cost control, governance and retraining.
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
As suas aulas são perfeitas. Adquiri o pacote de um ano e, finalmente, tenho a oportunidade de acompanhar diversos temas do meu interesse sem precisar mudar de plataforma... agradeço por tudo o que fazem, já recomendei vocês a outras pessoas...
Giulio CarloAluno de Marketing Digital
Eu gosto de como as lições são direto ao ponto e como eu consigo alterar capítulos e pular conteúdos que não preciso.
Mariana FerresAluna de Fotografia
Gosto do conteúdo e do modo de apresentação e transcrição de vídeos, o que acelera o processo!
Luciana AlvarengaAluna de Design de Unhas
A plataforma é rápida, simples de usar. A diversidade de conteúdo e os vídeos complementares ajudam muito no aprendizado.
Giulio CarloAluno de Engenharia de Prompt
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