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Data Science Machine Learning Course
Unlock the power wey dey inside data with our Data Science Machine Learning Course, wey we tailor give Business Intelligence professionals dem. Enter inside feature engineering matter, master time-based and domain-specific strategies well well. Sharpen your skills with data preprocessing, handle missing values well, and encode categorical variables proper. Learn machine learning algorithms like Decision Trees and Gradient Boosting. Learn how to train model, evaluate am, and deploy am, put all inside business processes smooth smooth. Make your BI expertise be on top with practical, high-quality insights.
- Master feature engineering: Create features wey dey impactful, wey dey specific to the domain.
- Deploy models seamlessly: Put inside business processes sharp sharp.
- Evaluate models precisely: Use RMSE, MAE, and cross-validation techniques proper.
- Preprocess data effectively: Clean am, encode am, and handle missing values well.
- Optimize algorithms: Tune hyperparameters and compare model performance well.

flexible workload of 4 to 360h
certificate recognized by the MEC
What will I learn?
Unlock the power wey dey inside data with our Data Science Machine Learning Course, wey we tailor give Business Intelligence professionals dem. Enter inside feature engineering matter, master time-based and domain-specific strategies well well. Sharpen your skills with data preprocessing, handle missing values well, and encode categorical variables proper. Learn machine learning algorithms like Decision Trees and Gradient Boosting. Learn how to train model, evaluate am, and deploy am, put all inside business processes smooth smooth. Make your BI expertise be on top with practical, high-quality insights.
Elevify advantages
Develop skills
- Master feature engineering: Create features wey dey impactful, wey dey specific to the domain.
- Deploy models seamlessly: Put inside business processes sharp sharp.
- Evaluate models precisely: Use RMSE, MAE, and cross-validation techniques proper.
- Preprocess data effectively: Clean am, encode am, and handle missing values well.
- Optimize algorithms: Tune hyperparameters and compare model performance well.
Suggested summary
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