Current

Intermediate

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Mathematics for Machine Learning and Data Science

Coursera · DeepLearning.AI · Updated March 2026

Platform rating

4.3/5

AI Tutor Rating

7.8/10

Duration

1-3 months

Classes

60

Master the mathematics behind machine learning including linear algebra, calculus, probability, and statistics from DeepLearning.AI.

What you'll get

Master linear algebra for machine learning

Apply calculus and optimization to neural networks

Use probability and statistics for ML rigorously

Course Curriculum

6 chapters

Fit

Best for

AI Researchers

PhD Students

Mathematicians

Frontier Scientists

Not ideal for

Learners seeking only entry-level overviews

Prerequisites & pricing

Prerequisites

High school math

Pricing

Subscription

Certification

Certificate

Growth Leverage: Completing this course opens avenues for roles such as Data Scientist, Machine Learning Engineer, and Quantitative Analyst. It also enhances eligibility for certifications like the Google Cloud Professional Data Engineer, positioning one for advanced career growth in AI-focused industries.

Skills Value: With expertise in linear algebra, calculus, and statistics, graduates can tackle complex data problems, justifying higher salaries that often exceed $100,000 annually in tech hubs. Employers value these skills for their direct impact on developing more effective machine learning models and data-driven insights.

Linear Algebra

Calculus

Probability

Statistics

Mathematics

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