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Introduction to Machine Learning For Data Science Course
Unlock di power wey data get with our "Introduction to Machine Learning for Data Science" course. Dis course tailor-make for Business Intelligence people dem. Enter inside important topics like how to prepare data, how to create better features, and how to train models. Master advanced algorithms like Random Forests and Gradient Boosting for predictin' sales. Learn how to make models perform betta wit hyperparameter tuning and how to measure dem using metrics like MAE and RMSE. Improve ya BI skills wit practical, high-quality information wey go drive business success.
- Master data cleaning: Make sure say data correct by removing anytin wey no dey right and any errors.
- Develop feature engineering: Create features wey get power to make model perform betta.
- Optimize models: Make models more accurate wit hyperparameter tuning and by comparing different algorithms.
- Visualize data insights: Use visualization tools to find information wey go help you take action.
- Evaluate models: Measure how well di model dey do by using metrics like MAE and RMSE.

from 4 to 360h flexible workload
certificate recognized by MEC
What will I learn?
Unlock di power wey data get with our "Introduction to Machine Learning for Data Science" course. Dis course tailor-make for Business Intelligence people dem. Enter inside important topics like how to prepare data, how to create better features, and how to train models. Master advanced algorithms like Random Forests and Gradient Boosting for predictin' sales. Learn how to make models perform betta wit hyperparameter tuning and how to measure dem using metrics like MAE and RMSE. Improve ya BI skills wit practical, high-quality information wey go drive business success.
Elevify advantages
Develop skills
- Master data cleaning: Make sure say data correct by removing anytin wey no dey right and any errors.
- Develop feature engineering: Create features wey get power to make model perform betta.
- Optimize models: Make models more accurate wit hyperparameter tuning and by comparing different algorithms.
- Visualize data insights: Use visualization tools to find information wey go help you take action.
- Evaluate models: Measure how well di model dey do by using metrics like MAE and RMSE.
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Before starting, you can change the chapters and 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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