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AI And Machine Learning Course
Advance your Business Intelligence career with our AI and Machine Learning Course. Become proficient in data preparation, covering formatting, managing missing values, and outlier treatment. Delve into predictive algorithms such as linear regression, decision trees, and sophisticated techniques like random forests. Fine-tune models using ensemble methods and hyperparameter tuning. Understand cross-validation, data splitting, and performance metrics. Improve your abilities in interpreting results and writing impactful reports. Enrol now for focused, top-notch learning designed for BI professionals.
- Become proficient in data cleaning: Handle missing values and outliers with accuracy.
- Implement ML algorithms: Apply linear regression and decision trees effectively.
- Fine-tune models: Improve performance through hyperparameter tuning and ensemble methods.
- Evaluate model accuracy: Use cross-validation and performance metrics like MAE and RMSE.
- Report insights: Develop compelling reports and confidently analyse model predictions.
flexible workload of 4 to 360h
certificate recognized by MEC
What will I learn?
Advance your Business Intelligence career with our AI and Machine Learning Course. Become proficient in data preparation, covering formatting, managing missing values, and outlier treatment. Delve into predictive algorithms such as linear regression, decision trees, and sophisticated techniques like random forests. Fine-tune models using ensemble methods and hyperparameter tuning. Understand cross-validation, data splitting, and performance metrics. Improve your abilities in interpreting results and writing impactful reports. Enrol now for focused, top-notch learning designed for BI professionals.
Elevify advantages
Develop skills
- Become proficient in data cleaning: Handle missing values and outliers with accuracy.
- Implement ML algorithms: Apply linear regression and decision trees effectively.
- Fine-tune models: Improve performance through hyperparameter tuning and ensemble methods.
- Evaluate model accuracy: Use cross-validation and performance metrics like MAE and RMSE.
- Report insights: Develop compelling reports and confidently analyse model predictions.
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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