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Artificial Intelligence Engineer Course
Boost your career prospects with our Artificial Intelligence Engineer Course, specifically designed for tech professionals keen to become proficient in AI. Delve into model training and assessment, explore data pre-processing techniques, and gain a thorough understanding of regression models. Learn to identify missing values in datasets, detect outliers, and fine-tune hyperparameters for optimal performance. Gain expertise in utilising model evaluation metrics such as MAE and MSE, and enhance your abilities in documentation and reporting practices. This comprehensive, high-quality course provides you with practical AI know-how to thrive in the tech sector.
- Become proficient in cross-validation techniques for reliable model evaluation.
- Conduct exploratory data analysis to discover valuable insights within datasets.
- Implement regression models to achieve accurate predictive outcomes.
- Optimise models using hyperparameter tuning methodologies.
- Document and report data pre-processing steps effectively.

flexible workload of 4 to 360h
certificate recognized by MEC
What will I learn?
Boost your career prospects with our Artificial Intelligence Engineer Course, specifically designed for tech professionals keen to become proficient in AI. Delve into model training and assessment, explore data pre-processing techniques, and gain a thorough understanding of regression models. Learn to identify missing values in datasets, detect outliers, and fine-tune hyperparameters for optimal performance. Gain expertise in utilising model evaluation metrics such as MAE and MSE, and enhance your abilities in documentation and reporting practices. This comprehensive, high-quality course provides you with practical AI know-how to thrive in the tech sector.
Elevify advantages
Develop skills
- Become proficient in cross-validation techniques for reliable model evaluation.
- Conduct exploratory data analysis to discover valuable insights within datasets.
- Implement regression models to achieve accurate predictive outcomes.
- Optimise models using hyperparameter tuning methodologies.
- Document and report data pre-processing steps effectively.
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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