Mathematics For Machine Learning Course
What will I learn?
Sharpen your Business Intelligence skills with our Mathematics for Machine Learning Course. Enter inside data exploration, and become master for the techniques to spot yawa (outliers) and handle data wey dey miss. Learn how to prepare data well, including how to normalize and treat yawa, so your model go dey more accurate. Explore machine learning algorithms wey dey work with time series, like decision trees and ARIMA. Become expert for feature engineering, how to make things work better (optimization techniques), and how to check if your model dey perform well. This course go give you correct, high-quality skills wey you fit use for real life work.
Apoia's Unique Features
Develop skills
Enhance your practical skills as listed below
Master how data dey arranged: Analyze and understand complex data sets well.
Detect yawa: Spot anything wey no follow (anomalies) so your data go dey more correct and reliable.
Apply time series models: Use ARIMA and LSTM to predict things with accuracy.
Make algorithms work better: Use gradient descent to train your model fast fast.
Engineer features: Create polynomial features to make your model perform better.
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 offers practical and relevant knowledge for your professional journey.