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Introduction to Machine Learning For Data Science Course

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What will I learn?

Unlock the power of data with our "Introduction to Machine Learning for Data Science" course, geared towards Business Intelligence professionals. Delve into key topics such as data pre-processing, feature engineering, and model training. Get to grips with advanced algorithms like Random Forests and Gradient Boosting for sales forecasting. Learn to optimise models through hyperparameter tuning and assess them using metrics like MAE and RMSE. Boost your BI skills with practical, high-quality insights that drive business success.

Apoia's Advantages

Online and lifetime access to courses
Certificate aligned with educational standards
Printable PDF summaries
Online support always available
Select and arrange the chapters you'd like to study
Set your own course workload
Instant feedback on practical activities
Study at your convenience, no internet required

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 change 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.