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AI for Tech

Linear Algebra

Learn how to analyze data rigorously using statistical methods to move beyond descriptive reporting and confidently validate business decisions with probability, inference, and hypothesis testing.
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Build the mathematical foundation required to implement machine learning models using vectorized computation and matrix operations in Python.
Duration
12 hours
Level
Beginner
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Who is this program for

Data analysts transitioning into predictive modeling and machine learning.
Junior data scientists seeking a deeper understanding of algorithm mechanics.
Machine learning engineers who want to master the math behind model optimization.
Software engineers entering the machine learning field.
Man wearing glasses and a black turtleneck sweater typing on a laptop at a wooden desk with a smartphone placed beside it.

Recommended prerequisites

* If you need to strengthen your Python fundamentals, you can refer to the course The Basics of Python for Data Analysis before starting this program.
You have experience writing and debugging basic Python scripts.
You are familiar with tabular data structures (DataFrames, arrays).
You understand fundamental algebra concepts (variables, equations, coordinate planes).
You have worked with data in tools like Excel or pandas.

Modules overview

6 Modules
Module 1. Vectors and vectors operations
Module 2. Distance between vectors
Module 3. Matrices and matrix operations
Module 4. Linear Regression from the inside
Module 5. Final project
Module 6. Final assessment

Get in touch!

You’re just one email away from transforming your company! Our team will reach out to understand your strategic objectives and craft a tailored solution that meets your specific needs.
Fill in the form
Learn about our product
Get a personalized offer for your business needs
We’ll reach out to understand your goals and craft a solution that works for you