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Introduction to Machine Learning For Data Science Course
Open di door to data power wit our 'Introduction to Machine Learning for Data Science' course, wey we make special for Business Intelligence people dem. Enter inside important topics like data wey dem don prepare, feature engineering, and how to train model. Master strong algorithms like Random Forests and Gradient Boosting for predict sales. Learn how to make model dem better through hyperparameter tuning and check dem with metrics like MAE and RMSE. Make your BI skills strong pass as e be wit correct, high-quality things wey you go see inside data wey go help business succeed.
- Master how to clean data: Make sure say e correct by comotting things wey no follow and errors.
- Develop feature engineering: Create features wey strong wey go make model work fine.
- Optimize models: Make am correct pass as e be with hyperparameter tuning and compare algorithm dem.
- Visualize data things wey you see inside: Use tools wey show picture to see things wey you fit do.
- Evaluate models: Measure how e work with metrics like MAE and RMSE.

flexible workload from 4 to 360h
certificate recognized by MEC
What will I learn?
Open di door to data power wit our 'Introduction to Machine Learning for Data Science' course, wey we make special for Business Intelligence people dem. Enter inside important topics like data wey dem don prepare, feature engineering, and how to train model. Master strong algorithms like Random Forests and Gradient Boosting for predict sales. Learn how to make model dem better through hyperparameter tuning and check dem with metrics like MAE and RMSE. Make your BI skills strong pass as e be wit correct, high-quality things wey you go see inside data wey go help business succeed.
Elevify advantages
Develop skills
- Master how to clean data: Make sure say e correct by comotting things wey no follow and errors.
- Develop feature engineering: Create features wey strong wey go make model work fine.
- Optimize models: Make am correct pass as e be with hyperparameter tuning and compare algorithm dem.
- Visualize data things wey you see inside: Use tools wey show picture to see things wey you fit do.
- Evaluate models: Measure how e work with metrics like MAE and RMSE.
Suggested summary
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