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Machine Learning r Course
Unlock the potential of Machine Learning with our detailed Machine Learning R Course, specifically created for statistics professionals in Pakistan. Delve into data pre-processing, gaining expertise in techniques like data splitting, feature scaling, and encoding categorical variables. Improve your abilities in data handling, exploratory data analysis, and model fine-tuning. Learn to implement algorithms such as Random Forests and Linear Regression, and evaluate models using cross-validation and metrics like R-squared. Enhance your expertise with practical, top-notch content designed for real-world applications relevant to the Pakistani context.
- Master data pre-processing: Split, scale, and encode data efficiently.
- Clean and handle data: Load, inspect, and manage missing values in R.
- Conduct EDA: Visualize distributions and effectively detect outliers.
- Fine-tune models: Optimise algorithms with hyperparameter tuning.
- Evaluate models: Use cross-validation and interpret performance metrics.

flexible workload from 4 to 360h
certificate recognized by the MEC
What will I learn?
Unlock the potential of Machine Learning with our detailed Machine Learning R Course, specifically created for statistics professionals in Pakistan. Delve into data pre-processing, gaining expertise in techniques like data splitting, feature scaling, and encoding categorical variables. Improve your abilities in data handling, exploratory data analysis, and model fine-tuning. Learn to implement algorithms such as Random Forests and Linear Regression, and evaluate models using cross-validation and metrics like R-squared. Enhance your expertise with practical, top-notch content designed for real-world applications relevant to the Pakistani context.
Elevify advantages
Develop skills
- Master data pre-processing: Split, scale, and encode data efficiently.
- Clean and handle data: Load, inspect, and manage missing values in R.
- Conduct EDA: Visualize distributions and effectively detect outliers.
- Fine-tune models: Optimise algorithms with hyperparameter tuning.
- Evaluate models: Use cross-validation and interpret performance metrics.
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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