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Introduction to Machine Learning For Data Science Course
Get ready to use data like a pro with our "Introduction to Machine Learning for Data Science" training, made special for people who work with Business Intelligence. We go deep into important things like cleaning up data, making new data features, and teaching computers how to learn. You'll become a master of powerful ways to predict sales, like Random Forests and Gradient Boosting. You'll also learn how to make these predictions even better by fine-tuning them and checking how good they are using things like MAE and RMSE. Boost your BI skills with real, top-quality understanding that helps businesses do well.
- Become a data cleaning expert: Make sure your data is correct by getting rid of mistakes and things that don't match.
- Get good at making new data features: Create strong features that make the computer learn better.
- Make predictions the best they can be: Improve how correct your predictions are by fine-tuning them and comparing different ways of learning.
- Show data insights in pictures: Use pictures and graphs to find useful things in the data.
- Check how good the predictions are: Measure how well your predictions are doing using things like MAE and RMSE.
from 4 to 360h flexible workload
certificate recognized by MEC
What will I learn?
Get ready to use data like a pro with our "Introduction to Machine Learning for Data Science" training, made special for people who work with Business Intelligence. We go deep into important things like cleaning up data, making new data features, and teaching computers how to learn. You'll become a master of powerful ways to predict sales, like Random Forests and Gradient Boosting. You'll also learn how to make these predictions even better by fine-tuning them and checking how good they are using things like MAE and RMSE. Boost your BI skills with real, top-quality understanding that helps businesses do well.
Elevify advantages
Develop skills
- Become a data cleaning expert: Make sure your data is correct by getting rid of mistakes and things that don't match.
- Get good at making new data features: Create strong features that make the computer learn better.
- Make predictions the best they can be: Improve how correct your predictions are by fine-tuning them and comparing different ways of learning.
- Show data insights in pictures: Use pictures and graphs to find useful things in the data.
- Check how good the predictions are: Measure how well your predictions are doing using things like MAE and RMSE.
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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