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Back to Probability & Statistics for Machine Learning & Data Science

Learner Reviews & Feedback for Probability & Statistics for Machine Learning & Data Science by DeepLearning.AI

4.6
stars
628 ratings

About the Course

Newly updated for 2024! Mathematics for Machine Learning and Data Science is a foundational online program created by DeepLearning.AI and taught by Luis Serrano. In machine learning, you apply math concepts through programming. And so, in this specialization, you鈥檒l apply the math concepts you learn using Python programming in hands-on lab exercises. As a learner in this program, you'll need basic to intermediate Python programming skills to be successful. After completing this course, you will be able to: 鈥� Describe and quantify the uncertainty inherent in predictions made by machine learning models, using the concepts of probability, random variables, and probability distributions. 鈥� Visually and intuitively understand the properties of commonly used probability distributions in machine learning and data science like Bernoulli, Binomial, and Gaussian distributions 鈥� Apply common statistical methods like maximum likelihood estimation (MLE) and maximum a priori estimation (MAP) to machine learning problems 鈥� Assess the performance of machine learning models using interval estimates and margin of errors 鈥� Apply concepts of statistical hypothesis testing to commonly used tests in data science like AB testing 鈥� Perform Exploratory Data Analysis on a dataset to find, validate, and quantify patterns. Many machine learning engineers and data scientists need help with mathematics, and even experienced practitioners can feel held back by a lack of math skills. This Specialization uses innovative pedagogy in mathematics to help you learn quickly and intuitively, with courses that use easy-to-follow visualizations to help you see how the math behind machine learning actually works.聽 We recommend you have a high school level of mathematics (functions, basic algebra) and familiarity with programming (data structures, loops, functions, conditional statements, debugging). Assignments and labs are written in Python but the course introduces all the machine learning libraries you鈥檒l use....

Top reviews

RR

Nov 13, 2023

Very good course! Highly recommended to those who are just starting to learn mathematics for machine learning

YG

May 22, 2025

It was very helpful course. It starts from the bare minimum but gradually you get to the point where you find yourself in Statistopia ???. Big applaud and thanks to Luis and also DeepLearning.AI

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76 - 100 of 127 Reviews for Probability & Statistics for Machine Learning & Data Science

By DuNo

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Mar 21, 2024

harder to understand than first two courses

By kaleem u

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Nov 12, 2023

Best course to learn Inferential Statistics

By Tilakraj G

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Dec 22, 2024

Excellent content and excellent instructor

By Ruoyan Q

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Sep 19, 2023

Great assignment, especially Week 1 and 4

By Aditi S

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May 14, 2024

this course Is good for data structures

By John P

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Oct 7, 2025

Great visualizations and explanations.

By Haiyun H

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Aug 22, 2023

wonderful courses, Thank you very much

By BHAGAVAN K

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Jan 20, 2025

Excellent course which I ever seen

By Arvasu G

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Sep 20, 2025

A complete and sufficient course

By Shaiq B

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Mar 15, 2025

Excellent foundational course.

By Sasyesh P S C

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Dec 9, 2024

Excellent and exceptional

By Andres F G A

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Jun 15, 2024

This course is a jewel!

By Marc D

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Jul 11, 2024

Excellent didactic!

By Ni P M O H P

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Sep 26, 2023

Thank You So Much!

By Damian O S B

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Sep 18, 2025

AWESOME COURSE !!

By Story B

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Sep 30, 2025

Well-structured

By sara m

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Jun 10, 2024

amazing course

By Anthony P

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Apr 13, 2025

Fantastic !!!

By Muhammad F F

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Mar 27, 2024

Good material

By Sabeur M

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Jan 15, 2024

Great cours

By Aini N

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Sep 21, 2023

its amazing

By Daniel G

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May 1, 2024

very nice

By Robert P

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Apr 13, 2025

AMAZING!

By Muhammad K I

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Mar 27, 2024

awesome