Listing this course as introductory with only algebra and functions from high school math as prerequisites is a huge reach, if not delusory.
There is a 0 probability that someone without prior linear algebra knowledge will be able to understand what is being taught on anything resembling an intuitive level. At best they will memorize rules without having any ability to derive or explain them.
This is my first experience with DeepLearning.AI and I am hugely dissapointed. I am using the course curriculum as guidelines for what to learn and going to Khan Academy instead.
List the course as what it actually is: a ML oriented refresher with linear algebra as a prerequisite.
I agree that Khan Academy has better Linear Algebra courses. But my suggestion would be not to give up on DeepLearning.AI just because of your disappointment with M4ML. That is not one of the core courses here. If you want to learn about Machine Learning, try the Machine Learning Specialization (MLS) followed by the Deep Learning Specialization (DLS). But for either of those, you need to be comfortable with linear algebra and python programming as prerequisites. Once you have completed your Khan Academy course on Linear Algebra, please consider having a look at MLS.
I actually have already provided this feedback on the pre-requisite for this course and specialisation. They would probably update this soon.
Thank you for feedback, I think so to learners do need to have some strong hold linear algebra, calculus and probability and statistics for m4ml specialisation which as far I remember the course instructor does mention but mentions it’s not mandatory. Instructor mentions if you learnt linear algebra, calculus in high-school, this should be good enough pre-requisite otherwise still not to worry.
The probability of this statement might be to inform and also encourage learner to brush up some of their high school math before taking up the course.
Thank you all for taking the time to respond and offer your perspectives. I am not giving on DL.AI as I have indeed heard great things about the MLS.
For the record, if that may help others in the future, I am supplementing my curriculum with “Why Machines Learn” by Anil Ananthaswamy and the 18.06SC linear algebra course by prof. Gilbert Strang on MIT opencourseware.
You are correct in your assessment that you do not have the relevant background to assess whether this course aligns with its stated prerequisites.
My comment’s aim is to suggest modifications to the course’s descriptions and prerequisites, so that other learners with the relevant background may have a positive experience with the course, knowing they should take it as a refresher and not as an introductory. For reference, 18.06SC from MIT Opencourseware (an actual introductory level course on linear algebra), suggests students should spend 150 hours on it. The linear algebra part of M4ML suggests 30 hours.
there is a category for learners to provide feedback on course, so whenever you want to provide any course related feedback, kindly select DeepLearning.AI Learning platform feedback in the category section.