Mathematics For Machine Learning Course
What will I learn?
Level up your Business Intelligence skills with our Mathematics for Machine Learning Course. Learn how to explore data, mastering the skills to spot outliers and deal with missing values. Learn data preprocessing, including normalisation and outlier treatment, to make your models more accurate. Explore machine learning algorithms for time series, like decision trees and ARIMA. Become an expert in feature engineering, optimisation techniques, and model evaluation. This course gives you practical, high-quality skills you can use in real life.
Apoia's Unique Benefits
Build skills
Enhance your practical skills in the areas listed below
Master data structures: Analyse and interpret complex data sets effectively.
Detect outliers: Identify anomalies to improve 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
Workload: between 4 and 360 hours
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
Examples of chapters you can add
You will be able to generate more chapters like the examples below
This is a free course, focused on personal and professional development. It is not equivalent to a technical, undergraduate, or postgraduate course, but it offers practical and relevant knowledge for your professional journey.