Introduction to Machine Learning For Data Science Course
What will I learn?
Get di power for use data well wit wi 'How to Start Machine Learning for Data Science' course, weh dem mek special for pipo weh de work wit Business Intelligence. Enter inside important topics like how to clean data, how to fix data features, and how to train model. Learn advanced ways like Random Forests and Gradient Boosting for predict sales. Learn how to make model betta wit hyperparameter tuning and check dem wit tins like MAE and RMSE. Make yu BI skills strong wit correct correct knowledge weh go help business succeed.
Apoia's Unique Features
Develop skills
Enhance the development of the practical skills listed below
Know how to clean data well: Make sure data correct by komot all mistake and problem.
Learn how to fix data features: Create good good features weh go make model work betta.
Make model betta: Make dem more correct wit hyperparameter tuning and compare algorithms.
See data clear clear: Use machine weh de show data for find tins weh man fit use.
Check model: Measure if e good wit tins like MAE and RMSE.
Suggested summary
Workload: between 4 and 360 hours
Before starting, you can adjust the chapters and the workload.
- Choose which chapter to begin with
- Add or remove chapters
- Adjust 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 growth. It is not equivalent to a technical, undergraduate, or postgraduate course, but offers practical and relevant knowledge for your professional journey.