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Introduction to Machine Learning For Data Science Course
Unlock di power weh data have wid wi 'Introduction to Machine Learning fi Data Science' course, tailor-made fi Business Intelligence professionals. Dive deep inna essential topics like data pre-processing, feature engineering, and model training. Master advanced algorithms dem like Random Forests and Gradient Boosting fi predict sales. Learn how fi optimize models through hyperparameter tuning and evaluate dem using metrics like MAE and RMSE. Boost yuh BI skills wid practical, high-quality insights weh drive business success.
- Master data cleaning: Mek sure di data accurate by tekkin out inconsistencies and errors.
- Develop feature engineering: Create powerful features fi mek di model perform betta.
- Optimize models: Improve accuracy wid hyperparameter tuning and comparing different algorithms.
- Visualize data insights: Use visualization tools fi find actionable insights.
- Evaluate models: Measure how successful di model is wid metrics like MAE and RMSE.

from 4 to 360h flexible workload
certificate recognized by the MEC
What will I learn?
Unlock di power weh data have wid wi 'Introduction to Machine Learning fi Data Science' course, tailor-made fi Business Intelligence professionals. Dive deep inna essential topics like data pre-processing, feature engineering, and model training. Master advanced algorithms dem like Random Forests and Gradient Boosting fi predict sales. Learn how fi optimize models through hyperparameter tuning and evaluate dem using metrics like MAE and RMSE. Boost yuh BI skills wid practical, high-quality insights weh drive business success.
Elevify advantages
Develop skills
- Master data cleaning: Mek sure di data accurate by tekkin out inconsistencies and errors.
- Develop feature engineering: Create powerful features fi mek di model perform betta.
- Optimize models: Improve accuracy wid hyperparameter tuning and comparing different algorithms.
- Visualize data insights: Use visualization tools fi find actionable insights.
- Evaluate models: Measure how successful di model is wid metrics like MAE and RMSE.
Suggested summary
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