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Machine Learning Course
Unlock the potential of machine learning with our comprehensive course tailored for technology professionals. Delve into data collection and exploration using Pandas and NumPy, master dataset splitting strategies, and evaluate models with accuracy. Learn crucial preprocessing techniques, explore advanced model selection methods, and gain insights into regression models like Decision Trees and Random Forests. Enhance your abilities with practical, high-quality content, ensuring you're well-prepared to address real-world problems. Enrol now and transform your career!
- Become proficient in data handling: Load, inspect, and select datasets using Pandas and NumPy.
- Implement dataset splitting: Apply cross-validation and stratified sampling approaches.
- Evaluate model performance: Understand MAE, MSE, and R-squared metrics thoroughly.
- Preprocess data effectively: Manage missing values and encode categorical variables skillfully.
- Optimize models: Fine-tune hyperparameters and utilise ensemble methods effectively.

flexible workload from 4 to 360h
certificate recognized by the MEC
What will I learn?
Unlock the potential of machine learning with our comprehensive course tailored for technology professionals. Delve into data collection and exploration using Pandas and NumPy, master dataset splitting strategies, and evaluate models with accuracy. Learn crucial preprocessing techniques, explore advanced model selection methods, and gain insights into regression models like Decision Trees and Random Forests. Enhance your abilities with practical, high-quality content, ensuring you're well-prepared to address real-world problems. Enrol now and transform your career!
Elevify advantages
Develop skills
- Become proficient in data handling: Load, inspect, and select datasets using Pandas and NumPy.
- Implement dataset splitting: Apply cross-validation and stratified sampling approaches.
- Evaluate model performance: Understand MAE, MSE, and R-squared metrics thoroughly.
- Preprocess data effectively: Manage missing values and encode categorical variables skillfully.
- Optimize models: Fine-tune hyperparameters and utilise ensemble methods effectively.
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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