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. Dive into essential topics like data preprocessing, 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 Unique Features
Develop skills
Enhance the growth 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 modify the chapters and the workload.
- Select which chapter to commence with
- Add or remove chapters
- Increase or decrease the course workload
Examples of chapters you can include
You’ll be able to generate additional chapters similar to the examples below
This is a free course focused on personal and professional growth. It does not equate to a technical, undergraduate, or postgraduate qualification, but offers practical and relevant knowledge for your professional journey.