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Mathematics For Machine Learning Course
Elevate your Business Intelligence skills with our Mathematics for Machine Learning Course. Dive into data exploration, mastering techniques to detect outliers and handle missing values. Learn data preprocessing, including normalisation and outlier treatment, to enhance model accuracy. Explore machine learning algorithms for time series, such as decision trees and ARIMA. Gain expertise in feature engineering, optimisation techniques, and model evaluation. This course equips you with practical, high-quality skills for real-world applications.
- Master data structures: Analyse and interpret complex data sets effectively.
- Detect outliers: Identify anomalies to enhance data accuracy and reliability.
- Apply time series models: Use ARIMA and LSTM for precise forecasting.
- Optimise algorithms: Implement gradient descent for efficient model training.
- Engineer features: Create polynomial features to improve model performance.

from 4 to 360h flexible workload
certificate recognized by MEC
What will I learn?
Elevate your Business Intelligence skills with our Mathematics for Machine Learning Course. Dive into data exploration, mastering techniques to detect outliers and handle missing values. Learn data preprocessing, including normalisation and outlier treatment, to enhance model accuracy. Explore machine learning algorithms for time series, such as decision trees and ARIMA. Gain expertise in feature engineering, optimisation techniques, and model evaluation. This course equips you with practical, high-quality skills for real-world applications.
Elevify advantages
Develop skills
- Master data structures: Analyse and interpret complex data sets effectively.
- Detect outliers: Identify anomalies to enhance data accuracy and reliability.
- Apply time series models: Use ARIMA and LSTM for precise forecasting.
- Optimise algorithms: Implement gradient descent for efficient model training.
- Engineer features: Create polynomial features to improve model performance.
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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