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Shahane Arushanyan

Phillip Morris International

About the course

This course has an aim to build a more substantial mathematical background for newcomers ready to pursue their careers in Machine Learning, combined with knowledge in programming with Python and the opportunity to apply their knowledge practically. You will work and learn with developer tools, data analysis tools, data visualization tools, and much more. The math part will cover Calculus, Linear Algebra, and Probability. This course is the first one and is followed by the Advanced Machine Learning course. After graduating from this one, students will be qualified to continue their studies in the advanced course with full or partial scholarships.

Learning Process


The topics will be covered in a diversified but logically structured order to make the learning process as efficient as possible. Most topics in the course are accompanied by practical knowledge intended for both in-class and homework assignments.

Lectures

Seminars

Homework

Get Qualified

The status of a graduate of this course will allow you to continue your studies on a deeper level and take the advanced Machine Learning course.

Gain practical knowledge

Students passing this course should display knowledge and the ability to solve complex problems and get familiar with practical tools.

Enrollment is open

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