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AI Mastery Course
Unlock the potential of artificial intelligence with our AI Mastery Course (Irish Edition), designed for technology professionals keen to get ahead. Delve into data understanding and exploration, mastering pattern identification and exploratory analysis. Hone your skills with data preprocessing, feature engineering, and model optimisation techniques. Learn to train and evaluate models using cutting-edge algorithms like decision trees and random forests. Wrap up with effective documentation and reporting, ensuring your AI projects are impactful and well-communicated.
- Master data exploration: Unearth patterns and anomalies in datasets.
- Optimise models: Boost performance with hyperparameter tuning and ensemble methods.
- Engineer features: Create and rank features for improved model accuracy.
- Evaluate algorithms: Compare models using precision, recall, and F1-score metrics.
- Document insights: Produce clear reports and present data-driven findings.

from 4 to 360h flexible workload
certificate recognized by the MEC
What will I learn?
Unlock the potential of artificial intelligence with our AI Mastery Course (Irish Edition), designed for technology professionals keen to get ahead. Delve into data understanding and exploration, mastering pattern identification and exploratory analysis. Hone your skills with data preprocessing, feature engineering, and model optimisation techniques. Learn to train and evaluate models using cutting-edge algorithms like decision trees and random forests. Wrap up with effective documentation and reporting, ensuring your AI projects are impactful and well-communicated.
Elevify advantages
Develop skills
- Master data exploration: Unearth patterns and anomalies in datasets.
- Optimise models: Boost performance with hyperparameter tuning and ensemble methods.
- Engineer features: Create and rank features for improved model accuracy.
- Evaluate algorithms: Compare models using precision, recall, and F1-score metrics.
- Document insights: Produce clear reports and present data-driven findings.
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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