Linear Algebra for Data Science Course
Gain mastery in linear algebra tailored for data science and business intelligence. Construct feature matrices, identify redundant data, deploy PCA for efficiency, and decode model weights to deliver precise predictions, minimise errors, and transform raw customer data into valuable business decisions that drive results.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This course equips you with essential linear algebra skills for data science, teaching you to create feature matrices, implement linear models, analyse weights, spot redundant features, and leverage PCA to simplify data. You'll master regularization techniques, dissect errors, and verify deployments, applying these directly to live data tasks for immediate impact.
Elevify advantages
Develop skills
- Build feature matrices from data tables into clean model inputs swiftly.
- Apply matrix models to fit and interpret predictions for key metrics.
- Spot multicollinearity using variance checks and decomposition techniques.
- Use PCA to cut dimensions, steady models, and boost training speed.
- Track live models for shifts, retrain as needed, and report to teams.
Suggested summary
Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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