Introduction to Machine Learning For Data Science Course
What will I learn?
Unlock the power of data with our "Introduction to Machine Learning for Data Science" course, tailored for Business Intelligence professionals. Delve into essential topics such as data pre-processing, feature engineering, and model training. Master advanced algorithms such as Random Forests and Gradient Boosting for sales prediction. Learn to optimise models through hyperparameter tuning and evaluate them using metrics like MAE and RMSE. Elevate your BI skills with practical, high-quality insights that drive business success.
Apoia's Differentials
Develop skills
Strengthen the development of the practical skills listed below
Master data cleaning: Ensure accuracy by removing inconsistencies and errors.
Develop feature engineering: Create impactful features for better model performance.
Optimise models: Enhance accuracy with hyperparameter tuning and algorithm comparison.
Visualise data insights: Use visualisation tools to uncover actionable insights.
Evaluate models: Measure success with metrics 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 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.