Introduction to Machine Learning For Data Science Course
What will I learn?
Open eye to the power wey dey inside data with our "Introduction to Machine Learning for Data Science" course, wey we tailor make e fit Business Intelligence people dem. Enter inside important topics like how to clean data well, how to make features wey go make sense, and how to train machine learning model. Learn how to use big algorithms like Random Forests and Gradient Boosting so you fit predict sales well. Learn how to make your models work sharp by tuning the hyperparameters and checking how good dem dey with metrics like MAE and RMSE. Make your BI skills blow with correct, high-quality knowledge wey go push business forward.
Apoia's Unique Features
Develop skills
Enhance the development of the practical skills listed below
Master data cleaning: Make sure say your data dey correct by removing any anyhow things and mistakes.
Develop feature engineering: Create features wey go make impact so your model go perform well.
Optimize models: Make your models dey accurate well well by tuning the hyperparameters and comparing algorithms.
Visualize data insights: Use visualization tools so you fit see things wey go help you take action.
Evaluate models: Measure how your model dey succeed with metrics like MAE and RMSE.
Suggested summary
Workload: between 4 and 360 hours
Before starting, you can modify the chapters and workload.
- Select which chapter to begin with
- Add or remove chapters
- Increase or decrease the course workload
Examples of chapters you can include
You can generate additional chapters like the examples below
This is a free course, aimed at 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.