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

4.6
stars
467 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

NP

Aug 8, 2023

Extraordinary course. With clear explanations and animation video. I learned Probability and statistics before but forgot a lot. This course helps me reinforce my knowledge about this subject as well.

AA

Sep 15, 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

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76 - 89 of 89 Reviews for Probability & Statistics for Machine Learning & Data Science

By Adek P D

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Sep 29, 2023

nice

By TAMPAN S

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Oct 10, 2023

-

By ADITYA V S

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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 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!

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 8, 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 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 Rahul R

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Mar 16, 2024

Last two weeks of the course are pretty hard to understand, it could've been made easier!

By Nguyễn V Q

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Jul 11, 2024

it very hard to learn

By Mehdi B H A

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Oct 29, 2024

A total waste of money and mostly time. So chaotic and hard to follow. really disappointed