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

4.6
stars
280 ratings

About the Course

Mathematics for Machine Learning and Data science is a foundational online program created by DeepLearning.AI and taught by Luis Serrano. This beginner-friendly program is where you’ll master the fundamental mathematics toolkit of machine learning. After completing this course, learners 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 struggle with mathematics. Challenging interview questions often hold people back from leveling up in their careers, and even experienced practitioners can feel held 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 plugins and visualizations to help you see how the math behind machine learning actually works. Upon completion, you’ll understand the mathematics behind all the most common algorithms and data analysis techniques — plus the know-how to incorporate them into your machine learning career....

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.

TJ

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.

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1 - 25 of 54 Reviews for Probability & Statistics for Machine Learning & Data Science

By Jong S

Jun 8, 2023

There were a few instances where wrong numbers in equations/slides (if everything is not correct, obviously I get confused as the learner), and there are some questions on the quiz that have not been addressed properly in the slides (i.e. using tables to look up z score values). Also lectures are incomplete (especially no lectures on MAP Estimation when previous videos clearly talk about it and it's even on the quiz). Would not recommend this course to anyone until it's been fully built out/properly reviewed.

By Ahmed A

Jul 4, 2023

While the outline of the course is promising, the explanation is far from reasonable or clear. Few things in the course that drove me nuts:

- Using several terminologies in the same exact video to refer to the same exact thing. For example: sigma + standard deviation, Gaussian distribution + Normal distribution. While technically this is not wrong, it is just confusing to keep up with what the instructor is referring to while you are trying to learn new concepts at the same time

- Using non-standard notation. In many videos the reference for mu, E[X] and variance used some notation that I did not manage to get hold on or find them being widely used in any other materials.

- Incorrect notations, beside the none standard, there were instances (I reported them to be reviewed) where the notation is plain wrong. For example summation over n = 1 to n = N of (E[X] - mu_x)^2 * P(x_i) What does it mean to have subscript for mu? do we have more than one mean? also where does the subscript i came from?

I am in the second week and I am sure I won't pass this course unless I used other learning materials to get better handle on the concepts

By Francesco M

Jul 1, 2023

This course gave me the impression that it was not created with the same attention as the other two in the specialization. There is a lot of things to learn but the lessons felt too fast and compressed.

Thdis course should either reduce the arguments or take its time to explain with longer/more videos and more intermediate labs and tests to make the experience more engaging.

By nagesh d

Jun 30, 2023

A good primer, but not the best to explain concepts. Putting a course together is one thing and actually making someone understand the concepts is a completely different animal. Very difficult to excel in making concepts clear.

By Brad F

Jun 2, 2023

This was another excellent course in an absolutely fantastic specialization track. The amount I learned per hour spent is far above any other specialization I've ever done. This will help me immensely in terms of career preparation.

By Marco C P S

Jun 9, 2023

Excelent course for those who want to get a deeper understanding on statistics and advanced analytics

By Ryan T

Aug 31, 2023

Probably the most difficult course in this specialization. Statistics and Probability is the branch of mathematics that challenges your intuition about data. But completing this felt rewarding. Well explained. Great labs.

By Kayvon P

Nov 15, 2023

Despite Luis's significant knowledge and teaching experience, the course wasn't as clear or easy to understand as it could have been. There were often chances for him to provide high level intuition behind new concepts like p-values or Z-statistics that he neglected to do, or did in an unintuitive way. And there were a number of verbal typos throughout the videos. A few specific points of feedback: Week 1 Lesson 2 - probability distributions Explanation of Bernoulli distribution was poor * Should have explained that a Bernoulli distribution is a special case of the binomial distribution with n = 1 Week 3 Lesson 1 - Central limit theorem - straightforward concept but really convoluted explanation. I found chatGPT’s explanation and example much more straightforward. Week 4 Lesson 1 - video 1 “For illustration's sake, imagine that you were taking a sample of size 1 and finding the mean of that sample to use as your estimate for the population mean. From the central limit theorem, you know that if you were to take multiple samples of this size and create a sampling distribution for the sample means for a sample of size 1. The sampling distribution of the sample means makes a gaussian with a center at mu and a standard deviation of sigma.” —> This is not true unless the underlying distribution is already normally distributed. Week 4 Lesson 2 - p-value lesson felt really rushed, especially the part on Z-statistic (unclear how to actually use it)

By Jose A P G

Jul 3, 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.

By Saicharan R C

Jun 5, 2023

The programming assignments were challenging. Especially Week 1. Worth the effort.

By Hugo M

Oct 17, 2023

Overall a solid course but there are things which could be made better. Let's talk about those first. I think the first half of the course is much better than the second. There are more in-video quizzes, and concepts are unpacked more intuitively. In the second half of the course a lot of times videos felt rushed, lots of formulas are just dumped on the screen without really explaining them and there is too much alternative (unexplained notation going on). In addition, some of the more complex topics just have reading, no video (like MAP). On the positive side most of the time Luis does a good job at explaining stuff intuitively and explaining how it relates to machine learning. Concepts are covered from multiple angles and are built from the ground up. The assignments are quite interesting and include exploring the birthday problem and A/B testing. Topics covered are quite broad: probability, Bayes theorem, hypothesis testing, confidence intervals, samples and population and probability distributions.

By Huy N

Jul 10, 2023

Need more exercises to practice

By Mariam A

Sep 2, 2023

The instructor mistakes a lot. Lots of information weren't explained clearly and sometimes skipped

By Nghĩa P

Aug 9, 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.

By Larry M

Feb 8, 2024

Excellent course. I studied probability and Stats long ago in university, but this course covered it in far greater depth.

By ABDUL M

Jun 26, 2023

It was a perfect course

By Dmytro N

Jun 6, 2023

Great materials, but would like more real-world examples

By Abraham O

Oct 30, 2023

Great course but the stats aspect was not so clear, also labs should be in the videos and instead of do on big lab assignment at the end, it should be in intervals, so after 4 videos do an assignment. But over all good course

By Marcus S

Feb 4, 2024

I took this to help prepare for my master's courses in ML, and I have to say, this helped me a lot. I was really surprised at the level of overlap from my master's courses and the content in this course. I think it did a really nice job explaining the notations, which I think is one of the biggest hurdles as to understanding statistics. I am very satisifed after taking this, and the items I learned in this course absolutely have application for the rest of my degree.

By Pranav A

Oct 1, 2023

Excellent course with detailed training videos, illustrations & labs. Good mix of mathematical concepts with Python code. Would highly recommend for a mathematical student to start with Machine learning. Special thanks to Louis (instructor) for the design & presentation of the course.

By Lihan T

Aug 16, 2023

I love all the courses in this specialization! I appreciate how you made complex problems seems much easier to comprehend and also show real world applications of them so they have context. Thank you for these great courses!

By Tanmay J

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.

By Gianni K B

Dec 20, 2023

Excellent course, I enjoyed every lesson, the teachers are great they explain complex concept in easy way I love it!!!

By Honza Z

Jul 18, 2023

Nice recap of what we should now from university. The way of explanation with using examples was really helpful.

By roy r r

Nov 13, 2023

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