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The course ‘Recursion, Backtracking and Dynamic Programming in Python’ offered on Coursera provides an in-depth exploration of some of the most fundamental and powerful algorithmic techniques used in computer science today. Covering a broad spectrum from basic recursion to advanced dynamic programming, the course is ideal for programmers looking to deepen their understanding of problem-solving strategies.
Starting with the essentials, the course explains recursion thoroughly, including stack memory management and common problems like Fibonacci numbers and the Tower of Hanoi. It then progresses into search algorithms such as linear and binary search, followed by selection algorithms like quickselect and median of medians, which are critical in various applications.
A significant highlight is the detailed treatment of backtracking, where classic puzzles like N-Queens and Sudoku are used to illustrate the technique. The course also dives into dynamic programming, teaching how to optimize solutions for problems like the knapsack, subset sum, and longest common subsequence.
Further, it covers advanced topics such as optimal packing and divide-and-conquer algorithms, exemplified by merge sort and the closest pair problem. The section on substring search algorithms like KMP and Rabin-Karp offers insights into efficient text searching techniques, essential for many real-world applications.
Finally, the course prepares students for real-world interviews with questions from major tech companies, along with an analysis of algorithm complexity using Big O, Omega, and Theta notations. Each section combines theoretical foundations with practical coding exercises in Python, ensuring learners gain hands-on experience.
Overall, this course is highly recommended for software engineers, computer science students, and tech professionals who want to master key algorithmic strategies. It’s comprehensive, well-structured, and practical, making complex concepts accessible and applicable.
Enroll Course: https://www.udemy.com/course/algorithmic-problems-in-python/