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Machine Learning r Course
Unlock the full power of machine learning with our well-detailed Machine Learning R Course, wey we design specially for oga and madam statisticians. Enter inside data preprocessing, and sabi correct techniques like how to split data, scale features, and encode categorical variables. Boost your skills for handling data, exploratory data analysis, and how to fine-tune models. Learn how to use algorithms like Random Forests and Linear Regression, and evaluate models using cross-validation and metrics like R-squared. Carry your expertise to another level with correct, high-quality content wey tailor-make for real-world use.
- Master data preprocessing: Split, scale, and encode data sharp sharp.
- Clean and handle data: Load data, check am well, and manage missing values for R.
- Conduct EDA: See how data dey spread and detect any anyhow data quick quick.
- Fine-tune models: Make algorithms work better with hyperparameter tuning.
- Evaluate models: Use cross-validation and check how the model dey perform.
from 4 to 360h flexible workload
certificate recognized by MEC
What will I learn?
Unlock the full power of machine learning with our well-detailed Machine Learning R Course, wey we design specially for oga and madam statisticians. Enter inside data preprocessing, and sabi correct techniques like how to split data, scale features, and encode categorical variables. Boost your skills for handling data, exploratory data analysis, and how to fine-tune models. Learn how to use algorithms like Random Forests and Linear Regression, and evaluate models using cross-validation and metrics like R-squared. Carry your expertise to another level with correct, high-quality content wey tailor-make for real-world use.
Elevify advantages
Develop skills
- Master data preprocessing: Split, scale, and encode data sharp sharp.
- Clean and handle data: Load data, check am well, and manage missing values for R.
- Conduct EDA: See how data dey spread and detect any anyhow data quick quick.
- Fine-tune models: Make algorithms work better with hyperparameter tuning.
- Evaluate models: Use cross-validation and check how the model dey perform.
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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