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ML Engineering Course
Become proficient in the core principles of machine learning engineering through our detailed ML Engineering Course. Created for tech professionals, this course provides a full understanding, starting from data collection and preparation, leading to model training, assessment, and practical implementation. Delve into recommendation systems, study machine learning algorithms, and learn how to incorporate live predictions into e-commerce platforms. Acquire hands-on abilities in scaling, documentation, and reporting, guaranteeing you're ready for genuine applications.
- Deploy models: Become skilled in scaling and live prediction in practice.
- Build recommendation systems: Explore different types and their use in e-commerce.
- Implement ML algorithms: Apply hybrid, content-focused, and collaborative approaches.
- Train and evaluate models: Understand precision, recall, and F1-score measures.
- Preprocess data: Identify data sources, encode, normalize, and manage incomplete data.

from 4 to 360h flexible workload
certificate recognized by MEC
What will I learn?
Become proficient in the core principles of machine learning engineering through our detailed ML Engineering Course. Created for tech professionals, this course provides a full understanding, starting from data collection and preparation, leading to model training, assessment, and practical implementation. Delve into recommendation systems, study machine learning algorithms, and learn how to incorporate live predictions into e-commerce platforms. Acquire hands-on abilities in scaling, documentation, and reporting, guaranteeing you're ready for genuine applications.
Elevify advantages
Develop skills
- Deploy models: Become skilled in scaling and live prediction in practice.
- Build recommendation systems: Explore different types and their use in e-commerce.
- Implement ML algorithms: Apply hybrid, content-focused, and collaborative approaches.
- Train and evaluate models: Understand precision, recall, and F1-score measures.
- Preprocess data: Identify data sources, encode, normalize, and manage incomplete data.
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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