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Maths for Data Science Course

Maths for Data Science Course
flexible workload of 4 to 360h
valid certificate in your country

What will I learn?

The Maths for Data Science Course equips learners with hands-on skills to clean retail order data, create revenue and profit metrics, and calculate vital descriptive statistics. It covers correlation, simple linear regression, and probability through straightforward numeric examples. By the end, you can convert quantitative analysis into clear, practical recommendations for business growth.

Elevify advantages

Develop skills

  • Master correlation and regression to link revenue, discounts, and profit quickly.
  • Gain fluency in descriptive statistics to summarise revenue and profit for better decisions.
  • Develop insights into probability to analyse order distributions and estimate key business odds.
  • Learn data preparation for retail by cleaning, validating, and transforming order CSV data.
  • Build skills in business storytelling with numbers to convert math results into clear recommendations.

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 classes are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of my interest without needing to change platforms... I thank you for everything you do, I've already recommended you to other people...
Giulio Carlo
Giulio CarloDigital Marketing Student
I like how the lessons are straight to the point and how I can change chapters and skip content that I don't need.
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Mariana FerresPhotography Student
I like the content and the way of presentation and video transcription, which speeds up the process!
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Luciana AlvarengaNail Design Student
The platform is fast, simple to use. The diversity of content and complementary videos help a lot in learning.
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André FelipePrompt Engineering Student

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