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Machine Learning Course
Unlock the power of Machine Learning with our well-detailed training wey dem design for tech gurus like you. Enter inside data collection and exploration using Pandas and NumPy, sabi how to split data well-well, and evaluate your models like a pro. Learn correct preprocessing techniques, explore better model selection, and get better understanding of regression models like Decision Trees and Random Forests. Sharpen your skills with correct, top-notch content wey go make sure say you dey ready to face any challenge wey come your way. Join us now make you change your career!
- Master data handling: Load, inspect, and select datasets using Pandas and NumPy.
- Implement dataset splitting: Apply cross-validation and stratified sampling techniques to split your data.
- Evaluate model performance: Understand MAE, MSE, and R-squared metrics wey dem dey use.
- Preprocess data effectively: Learn how to handle missing data and change categorical variables to numbers.
- Optimize models: Tune hyperparameters and use ensemble methods to make your models better.

from 4 to 360h flexible workload
certificate recognized by MEC
What will I learn?
Unlock the power of Machine Learning with our well-detailed training wey dem design for tech gurus like you. Enter inside data collection and exploration using Pandas and NumPy, sabi how to split data well-well, and evaluate your models like a pro. Learn correct preprocessing techniques, explore better model selection, and get better understanding of regression models like Decision Trees and Random Forests. Sharpen your skills with correct, top-notch content wey go make sure say you dey ready to face any challenge wey come your way. Join us now make you change your career!
Elevify advantages
Develop skills
- Master data handling: Load, inspect, and select datasets using Pandas and NumPy.
- Implement dataset splitting: Apply cross-validation and stratified sampling techniques to split your data.
- Evaluate model performance: Understand MAE, MSE, and R-squared metrics wey dem dey use.
- Preprocess data effectively: Learn how to handle missing data and change categorical variables to numbers.
- Optimize models: Tune hyperparameters and use ensemble methods to make your models better.
Suggested summary
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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