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Linear Algebra for Data Science Course

Linear Algebra for Data Science Course
from 4 to 360h flexible workload
valid certificate in your country

What will I learn?

This Linear Algebra for Data Science Course equips you with practical tools to construct, comprehend, and enhance predictive models. You will learn to build feature matrices, implement linear models, analyse weights, spot redundancy, and employ PCA for dimensionality reduction. Additionally, you will engage in regularization, error assessment, and deployment verification, acquiring skills applicable right away to actual data initiatives.

Elevify advantages

Develop skills

  • Build feature matrices: convert BI tables into neat X and y for swift modelling.
  • Model with matrices: formulate, fit, and analyse linear models for BI KPIs.
  • Detect multicollinearity: utilise XᵀX, VIF, and SVD to identify redundant BI features.
  • Apply PCA in BI: diminish dimensions, steady models, and accelerate training.
  • Monitor models in production: observe drift, retrain, and clarify results to stakeholders.

Suggested summary

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.
Workload: between 4 and 360 hours

What our students say

Your lessons are perfect. I got the one-year package and finally have the chance to follow several topics I'm interested in without having to switch platforms... thank you for everything you do, I've already recommended you to others...
Giulio Carlo
Giulio CarloDigital Marketing Student
I like how the lessons get straight to the point and how I can switch chapters and skip content I don't need.
Mariana Ferres
Mariana FerresPhotography Student
I like the content and the way the videos are presented and transcribed, which speeds up the process!
Luciana Alvarenga
Luciana AlvarengaNail Design Student
The platform is fast and easy to use. The variety of content and the extra videos really help with learning.
Giulio Carlo
Giulio CarloPrompt Engineering Student

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