Here's how you can effectively practice algorithm interview questions.

After passing algorithm-based interviews, here are quick tips from my experience: ?? Understand basic data structures and solving patterns: Learn arrays, strings, linked lists, trees, hashmaps, and greedy approaches. ?? ?? Start with single tasks to develop pattern recognition and problem-solving skills. ?? ?? Focus on common questions from sites like LeetCode (top 75 problems) for clear descriptions and good starting points. ?? ?? Learn from others by comparing your solutions with theirs—valuable insights come for free. ?? Above all, never give up, keep practising, and celebrate your progress! ??

Make sure you know what are the different types of sorting, what "costs" what, which algo is relevant and when. Also, when it comes to algorithmic questions, make sure you know what are the different types of data structure, e.g. a hashmap, a dict, a list, linked list, array, etc. It will really help you understand and solve these kind of Q's.

1.Start with basics - understand algorithms, how they work, why important. Learn common easy types like sorting, searching, dynamic programming. 2.Practice problems - begin easy, like basic sorting, progress to complex data structures, techniques. 3.Regularly revise - revisit solved problems, concepts, important point of a algorithms. 4.Dive into data structures - arrays, linked lists, trees, graphs. Understand operations, complexities for each. 5.Learn algorithmic techniques - divide-and-conquer, greedy, dynamic programming. 6. Analysis - focus on problem analysis, identifying right approaches, optimizing solutions. 7. Ensure proficient coding - write clean, efficient, readable code in preferred language.

Make sure you have a strong grasp of basic algorithms and data structures such as arrays, linked lists, stacks, queues, trees, graphs, hash tables, sorting, and searching algorithms. Be comfortable analyzing the time and space complexity of different algorithms using Big O notation.

Dedicate a specific amount of time each day to solving algorithm problems. Consistency is key to improvement. Work on problems of varying difficulties to build confidence and challenge yourself.

Practice solving problems within a specific time limit to simulate the pressure of a real interview. Practice explaining your thought process and solution as if you were in a real interview. This will help you communicate more effectively during the actual interview. Participate in mock interviews with friends, mentors, or use platforms like Pramp and Interviewing.io to get a feel for the real interview environment.

Keep a record of the problems you’ve solved, noting the approaches you took and any difficulties you encountered. Regularly review your journal to identify patterns in your mistakes or areas where you need improvement.

Understand what types of algorithms the team is working on, what is their focus (speed, accuracy..) and what frame works they typically use. Then, you can recall solutions from your studies, SOTA publications and the tradeoffs of these vs older ones. For example, a newer solution may require a larger AI-model which may require a newer GPU, but it it is more generalizable. Coding wise, review which implementations are there and which are patent protected.