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Back to Calculus for Machine Learning and Data Science

Learner Reviews & Feedback for Calculus for Machine Learning and Data Science by DeepLearning.AI

4.8
stars
893 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, learners will be able to: 鈥� Analytically optimize different types of functions commonly used in machine learning using properties of derivatives and gradients 鈥� Approximately optimize different types of functions commonly used in machine learning using first-order (gradient descent) and second-order (Newton鈥檚 method) iterative methods 鈥� Visually interpret differentiation of different types of functions commonly used in machine learning 鈥� Perform gradient descent in neural networks with different activation and cost functions 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

AA

Sep 16, 2024

this course is perfect and its also a necessary step in learning machine learning it helped me learn how calculus affects on optimization and how I can implement them using python

MS

Aug 30, 2023

very good courses. The material is quite deep and difficult, but can be conveyed so that it is easy to understand. The lab is also very helpful to better understand the concept

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126 - 150 of 187 Reviews for Calculus for Machine Learning and Data Science

By Varun M

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May 27, 2023

Amazing Course

By Orhan S

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Jul 3, 2023

Great course!

By Kristaps F

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Feb 23, 2024

Very useful

By Sabeur M

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Jan 15, 2024

Great cours

By MARC F

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Apr 19, 2023

So awesome!

By Javier A P S

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May 31, 2025

super bien

By Its M

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Nov 30, 2024

Excellent.

By Mahmoud D

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Jan 18, 2025

Excellent

By Pawel P

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May 16, 2024

Thank you

By Jose M

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Nov 16, 2023

Excelent!

By Pranay V

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Apr 5, 2025

its good

By Renan d B L

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Jul 20, 2024

Amazing!

By Abdul R W

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Sep 22, 2023

done all

By emerson g

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Aug 7, 2023

The Best

By Deepak K

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Mar 30, 2023

good one

By DARPAN B

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Jul 4, 2025

amazing

By Muhammad K I

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Mar 27, 2024

awesome

By Trisno P R

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Sep 25, 2023

jossss

By Alvin F P

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Mar 24, 2024

great

By Moaaz m

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Aug 6, 2025

good

By Anggi P S

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Mar 24, 2024

good

By Nidula R

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Jul 6, 2023

good

By Collins N

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Aug 7, 2024

..

By Nurullah K

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Jun 26, 2024

It was good untill week 3. My real point is 3.5 . I think this spec is definitely not a math course. they just show the math parts of the ML , they are just telling ML terms, this is a calculus course but subjects are what a neural network is, what a gradient descent is , or network method etc. Where exactly math here? There is no need if you dont tell it comrehensively , Every tutor is teaching much more math than this spec in any ML course. You are telling %10 percent math and then %90 percent ML terminology. Why do i have to learn what a neural network even with more than two layer in a math course. Then what are you gonna tell me in the ML course??? if you will, then make it like first two weeks. It was like equally math and ML but in week 3 it is %90 like an ML Course.

By Kevin W

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Jul 10, 2024

Overall, it is an excellent introduction to calculus and applications to ML. However, some of the foundational explanations of differentiation need clarification. If you want a rigorous introduction to calculus, I recommend Khan's Academy. For example: in Khan's, you will find an in-depth explanation of limits which is only touched upon briefly in this course.