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

4.6
stars
518 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’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....

Top reviews

AA

Sep 16, 2024

this course is amazing! this course teachs how important probabilities is in machine learning and covers alots of topics where probabilities and statistics are useful in machine learning

TJ

Sep 23, 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.

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76 - 100 of 104 Reviews for Probability & Statistics for Machine Learning & Data Science

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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Apr 30, 2024

very nice

By Muhammad K I

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Mar 27, 2024

awesome

By Nanda P N N

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Mar 22, 2024

COOLLLL

By Dwiki H

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Sep 29, 2023

so cool

By KURRA V T

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Jan 21, 2025

SUPERB

By Ni K P S

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Sep 28, 2023

Great!

By Daniel K

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Apr 14, 2024

great

By KURELLA R

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Sep 17, 2024

GOOD

By syabiroe

•

Nov 30, 2023

nice

By Alif W S

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Oct 2, 2023

Good

By Adek P D

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Sep 30, 2023

nice

By TAMPAN S

•

Oct 10, 2023

-

By ADITYA V S

•

Aug 6, 2024

Indepth and apt knwoledge about probability and statistics and their use-case in real life situations such as using confidence intervals which help you to understand the variablility, precision and reliability of your estimates. Also it has hypothesis testing that allows to verify your hypothesis based on data. Overall a very good course.

By Ericy

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Jun 18, 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!

By Anshul Y

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Jul 2, 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.

By Hadar D S (

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Jul 5, 2024

This is definitely the hardest course in this specialization. It's definitely interesting and will help me a lot at school.

By Evert J K

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Nov 12, 2024

Good course and gives a good understanding!

By Nenda M K M

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Oct 9, 2024

good course

By Yuganshu

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Feb 4, 2024

I am rating this course 3 stars because I had to struggle a lot in understanding the concepts of statistics even after reviewing the lectures. The pace should have been slower and the terminologies discussed were not very clear. This course took me 10 days extra to complete.

By Balu V

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Dec 18, 2024

This course is the most challenging to understand in the specialization. There are numerous equations that, according to ChatGPT, have simple meanings. However, the lack of repetition and the rushed pace made me listen to the videos multiple times to grasp the topics.

By Beyers S

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Jan 22, 2024

Cannot finish this course, as my Python skills are lacking - yet, the course was advertised as for "beginners". I tried to submit my first programming assignment about 30 times, no success. Very disappointed.

By andrew g

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Apr 12, 2024

Fine. Didn't mention anything about ML so you'll just have to figure out how this relates on your own.

By Michal S

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Feb 4, 2025

While I really enjoyed most of the courses, the last week content was rushed and difficult to digest.