I am reading the book "Introduction to Algorithms", 4th edition, by Thomas H. Corman, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein to learn relevant knowledge related to algorithms and data structure for data science. I will add context in the next paragraph but I just want to know what parts of the books I should focus on in terms of chapters. I would add a screenshot of the book's table of contents itself but the book is spread across 4-5 pages so it seems impractical to do so.
Now adding context: My goal is to eventually work as either an ML engineer/AI engineer/Data Analyst or less precisely under the umbrella term as a data scientist. I know programming in Python to the extent that I can implement certain models, but I do not think I have done enough to really stand out. For further context, I am a Mathematics undergraduate in my 4th year, so if there is anything that might overlap with I may have learned before, knowing that would be nice too.
Thanks in advance.
