Back to Probability & Statistics for Machine Learning & Data Science
DeepLearning.AI

Probability & Statistics for Machine Learning & Data Science

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’ll 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: • Describe and quantify the uncertainty inherent in predictions made by machine learning models, using the concepts of probability, random variables, and probability distributions. • Visually and intuitively understand the properties of commonly used probability distributions in machine learning and data science like Bernoulli, Binomial, and Gaussian distributions • Apply common statistical methods like maximum likelihood estimation (MLE) and maximum a priori estimation (MAP) to machine learning problems • Assess the performance of machine learning models using interval estimates and margin of errors • Apply concepts of statistical hypothesis testing to commonly used tests in data science like AB testing • 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.  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’ll use.

Status: Statistical Modeling
Status: Statistical Visualization
IntermediateCourse33 hours

Featured reviews

RR

5.0Reviewed Nov 12, 2023

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

S

5.0Reviewed Jan 15, 2024

Perfect blend of Math and Python to have a Deep Basic foundation in Machine Learning and Data Science

YG

5.0Reviewed May 21, 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

EE

4.0Reviewed Jun 17, 2024

Very thorough and easy to comprehend approach to learning statistical and probability theory which is important foundational knowledge, not just in ML but any field of data analytics!

HH

5.0Reviewed May 2, 2024

Thanks DeepLearning.AI for creating this specialization. I went from the guy that everytime i hear the word 'math i'd freakout to 'math is my lover'. Once again thank you for everything

JP

5.0Reviewed Jul 2, 2023

It was a super exciting journey through maths. My last courses in my were 20 years ago, and it was easy to follow and remember all these topics.

MB

5.0Reviewed Mar 8, 2025

The course is very organized. It helped me go through the basics I needed with ML & DS in focus on how and why every part is used in ML applications.

TJ

5.0Reviewed Sep 22, 2023

The course was very detailed and interactive, which made learning about statistics and probability easy. The engaging visuals were a great aid in understanding the concepts.

AY

4.0Reviewed Jul 1, 2024

I think graded quiz was good, but the programming assignments could be made more challenging to have a good understanding of python and math simultaneously.

MR

5.0Reviewed Jun 1, 2024

Very nicely explained. Lab assignments provide a great opportunity to implement the concepts learnt on real world use cases.

RM

5.0Reviewed Jan 3, 2025

It was a great learning experience, and all the examples were carefully chosen with a special focus on machine learning. Well done and thank you!

JK

5.0Reviewed Oct 4, 2023

Best Course for statistics beginners. It saves tons of hours from digging book or sources.

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