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学生对 DeepLearning.AI 提供的 Linear Algebra for Machine Learning and Data Science 的评价和反馈

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2,148 个评分

课程概述

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: • Represent data as vectors and matrices and identify their properties using concepts of singularity, rank, and linear independence, etc. • Apply common vector and matrix algebra operations like dot product, inverse, and determinants • Express certain types of matrix operations as linear transformations • Apply concepts of eigenvalues and eigenvectors to machine learning problems 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....

热门审阅

NA

Jun 17, 2023

Very visual and application oriented and gives the context for machine learning and where linAL is applied in PCA and neural networks. The structure is really byte sized and fun to work with.

SP

Jul 26, 2023

This course is truly exceptional for individuals eager to strengthen their grasp of Linear Algebra concepts, paving the way for a deeper understanding of machine learning and data science.

筛选依据：

501 - Linear Algebra for Machine Learning and Data Science 的 514 个评论（共 514 个）

创建者 invk007

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Sep 9, 2025

- Bad audio quality - Poor quality ai generated transcription and translations to other languages - The instructor skips important material - Many unclear parts are not explained properly - Overpriced labs

创建者 Travis R

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Jul 26, 2025

It is very frustrating when you have to go do research outside of a Non-Credit class to understand what they are talking about. It started off so well then was almost like they wanted this rushed.

创建者 Vlad P

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Oct 31, 2023

Very poor explanation. The tutor more practises tongue twisters, than actually explains anything. You'll definitely need other sources of information to understand the topic.

创建者 Tse K Y C

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May 10, 2024

While I love to learn, but the course keeps changing its content and assignments, never ending in a matter of couple months and couple of days.

创建者 Supun W

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Jan 24, 2024

worst experience i have ever had with a course on coursera. because of the week 3 lab assignment errors i could not finish the course.

创建者 Abtin T

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Dec 20, 2023

Teaching is hard to understand. It is not as good as described in the teacher's introduction.

创建者 Frank w

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Jul 23, 2023

The course doesn't cover detailed computation but those were tested in assignments

创建者 Sepehr D

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Jul 14, 2025

not suitable for those who want to understand linear algebra deeply

创建者 Ikram A

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Nov 4, 2023

only 1 star because, the quiz labs are not working properly.

创建者 Atharva P

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Aug 7, 2023

Worst Linear Algebra course with all wrong coding solutions.

创建者 Hana A S A

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Dec 21, 2024

انحذفت عندي الاكواد في المختبر وما قدرت ارجعها

创建者 Nivethitha S

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Oct 13, 2023

Last week 4 assignment didn't submitted

创建者 Cameron S D

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May 11, 2023

Won't let me un-enroll!

创建者 Ehsan s

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May 19, 2024

poor content delivery.