Introduction to Machine Learning For Data Science Course
What will I learn?
Get di power from data wit wi class, 'How to Learn Machine Learning for Data Science,' we mek special for people weh work wit Business Intelligence. You go dig inside important topics like how to prepare data, how to build good features, and how to train machine learning model. You go learn how to use strong machine learning method them like Random Forests and Gradient Boosting for know how much sales you go get. You go learn how to mek model them work betta by fine-tune them and check if dem good by use metric them like MAE and RMSE. Mek your BI skills strong wit real, good sense weh go help your business succeed.
Apoia's Unique Features
Develop skills
Enhance your practical skills in the areas listed below.
Learn how to clean data good-good: Mek sure say all di data dey correct by troway all di mistake and bad data.
Learn how to build feature dem: Build good feature dem weh go mek model dem work betta.
Mek model dem work betta: Mek dem more correct by fine-tune dem and compare method them.
See di data for understand am: Use picture dem to find thing dem weh you can use for mek decision.
Check if model dem good: Measure how dem dey succeed by use metric them like MAE and RMSE.
Suggested summary
Workload: between 4 and 360 hours
Before starting, you can modify 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.