Math Self-Study: Build a Strong Foundation for AI PhD

In summary, the goal is to build a strong mathematical foundation, and the books recommended are: Savov - No Bull**** Guide to Math and Physics, Velleman - How to Prove it, Spivak - Calculus, Axler - Linear Algebra Done Right, Mendelson - Introduction to Topology, Kleene - Mathematical Logic, Graham - Concrete Mathematics, Ghorpade - Course in Multivariable Calculus and Analysis, Rudin - Principles of Mathematical Analysis, Pinter - Abstract Algebra, Farlow - PDE for Scientists and Engineers.
  • #1
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Hi, I'm embarking on a mission to self-study math, and would like some recommendations on any missing books or ones that should be replaced in my repertoire.

The goal is to build a strong mathematical foundation. My naive idea of what that means is something like an undergraduate math major, so I have googled a bit to get an idea of the relevant areas, and searched amazon for the best books on those topics, this is what I have so far:

Savov - No Bull**** Guide to Math and Physics
Velleman - How to Prove it
Spivak - Calculus
Axler - Linear Algebra Done Right
Mendelson - Introduction to Topology
Kleene - Mathematical Logic
Graham - Concrete Mathematics
Ghorpade - Course in Multivariable Calculus and Analysis
Rudin - Principles of Mathematical Analysis
Pinter - Abstract Algebra
Farlow - PDE for Scientists and Engineers

My long-LONG term goal is a PhD in CS, specifically AI. So please advice me! Keep in mind that I'm really starting from basics here, as I'm currently only 7/10 through Khan Academy and nothing more.
 
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  • #2
Most students arrive at college with weak algebra and trig skills.

Don't waste your time with those books before you have completed the ALEKS pre-calculus course (online) to make sure you are ready.
 
  • #3
My idea was to master the World of Math mission on Khan Academy [0] before starting books. That program includes pre/calculus, so if I can complete it, that would indicate that I'm ready to start some of those books, don't you agree?

[0] https://www.khanacademy.org/math
 
  • #4
I'm not entirely sure it would, to be honest. Khan academy doesn't have enough practice questions, and the ones it does have aren't very challenging.

Plus, I don't believe video lectures replace learning straight out of a textbook at all. You're not always going to have Khan to hold your hand throughout difficult concepts. Especially if Michael Spivak is going to be your first exposure to calculus.
 
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  • #5
I also think you need a lot of practice and validated assessments of learning. ALEKS has that.

A lot of math departments have validated and confirmed that ALEKS pre-calc ensures readiness for calculus.
 
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  • #6
KiggenPig said:
I'm not entirely sure it would, to be honest. Khan academy doesn't have enough practice questions, and the ones it does have aren't very challenging.

Plus, I don't believe video lectures replace learning straight out of a textbook at all. You're not always going to have Khan to hold your hand throughout difficult concepts. Especially if Michael Spivak is going to be your first exposure to calculus.
What do you mean by not enough practice questions? As in variety, or difficulty? Because KA keeps generating new questions forever until the student gets it right enough times.

And in my plan Spivak would not be the first exposure, I was thinking KA -> Savov No BS Guide -> Velleman Proofs -> Spivak.

But please tell me bluntly if this is a bad idea, because I'm here to find advice for the best learning path!
 
  • #7
Hello, I'm currently working myself through Spivak, and that was after I've worked through most of "Book of Proof"; even then Spivak proved to be exceedingly tough. It is really a whole other ball game compared to anything you may have learned in school. I'm not sure about the "No BS Guide" since I've never heard of it, but I strongly suggest you follow Dr Courtney's advice, you need to be very good at Algebra and Trig, I learned that the hard way by trying to overcome rigorous Math without said skills. If you would like a book instead of using ALEKS you could try Mathematics: The Core Course for A-level
 
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lordianed said:
Hello, I'm currently working myself through Spivak, and that was after I've worked through most of "Book of Proof"; even then Spivak proved to be exceedingly tough. It is really a whole other ball game compared to anything you may have learned in school. I'm not sure about the "No BS Guide" since I've never heard of it, but I strongly suggest you follow Dr Courtney's advice, you need to be very good at Algebra and Trig, I learned that the hard way by trying to overcome rigorous Math without said skills. If you would like a book instead of using ALEKS you could try Mathematics: The Core Course for A-level
Thanks, I will take your advice under consideration, and add the book to my list of potential study material.

I think the "No BS Guide" seems good since it supposedly takes the reader from high school math to calculus, and everyone on amazon is singing high praise in the reviews, so if they are honest reviews then it seems like a good book to start with.
 

Related to Math Self-Study: Build a Strong Foundation for AI PhD

What is the purpose of "Math Self-Study: Build a Strong Foundation for AI PhD"?

The purpose of "Math Self-Study: Build a Strong Foundation for AI PhD" is to provide a comprehensive and rigorous study guide for individuals who are interested in pursuing a PhD in artificial intelligence. This program focuses specifically on building a strong foundation in mathematics, which is essential for understanding and conducting research in AI.

Who is this program designed for?

This program is designed for individuals who have a strong interest in artificial intelligence and are planning to pursue a PhD in this field. It is also suitable for those who have a background in mathematics and want to strengthen their skills in preparation for an AI PhD program.

What topics are covered in this self-study program?

This program covers a wide range of mathematical topics that are essential for understanding and conducting research in AI. Some of the topics include linear algebra, calculus, probability and statistics, algorithms, and optimization.

Do I need any prior knowledge or experience in math to benefit from this program?

While prior knowledge and experience in math can be helpful, it is not a requirement for this program. The program is designed to start from the basics and build a strong foundation in math, so individuals with little to no background in math can still benefit from it.

How will this self-study program prepare me for an AI PhD program?

This program will provide you with a solid understanding of the mathematical concepts and tools that are essential for AI research. It will also help you develop critical thinking and problem-solving skills, which are crucial for success in a PhD program. Additionally, completing this program will demonstrate your dedication and readiness for pursuing an AI PhD to admissions committees.

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