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Python With Machine Learning Course
Unlock the power of Python and machine learning with our comprehensive course, custom-made for technology professionals like yourself. Get stuck into feature engineering, mastering scaling, normalisation, and dealing with categorical variables. Sharpen your skills with model optimisation techniques like random search and hyperparameter tuning. Explore data sources from UCI and Kaggle, and become a pro with algorithms such as random forests and decision trees. Take your expertise to the next level with practical, top-notch training designed for real-world application.
- Master feature engineering: Scale, normalise, and create time-based features.
- Optimise models: Learn hyperparameter tuning and grid search techniques.
- Source data effectively: Make use of UCI and Kaggle for relevant datasets.
- Implement algorithms: Explore Random Forests, Decision Trees, and Linear Regression.
- Evaluate models: Use MAE, RMSE, and data splitting for performance analysis.

from 4 to 360h flexible workload
certificate recognized by MEC
What will I learn?
Unlock the power of Python and machine learning with our comprehensive course, custom-made for technology professionals like yourself. Get stuck into feature engineering, mastering scaling, normalisation, and dealing with categorical variables. Sharpen your skills with model optimisation techniques like random search and hyperparameter tuning. Explore data sources from UCI and Kaggle, and become a pro with algorithms such as random forests and decision trees. Take your expertise to the next level with practical, top-notch training designed for real-world application.
Elevify advantages
Develop skills
- Master feature engineering: Scale, normalise, and create time-based features.
- Optimise models: Learn hyperparameter tuning and grid search techniques.
- Source data effectively: Make use of UCI and Kaggle for relevant datasets.
- Implement algorithms: Explore Random Forests, Decision Trees, and Linear Regression.
- Evaluate models: Use MAE, RMSE, and data splitting for performance analysis.
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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