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In this Introduction to Algorithms in Python course, you’ll learn about algorithm basics like recursion and then go all the way to working with concepts like dynamic programming. The 5 main course segments include simple recursive algorithms, data structures, divide & conquer, greedy algorithms, and dynamic programming. ✏️ Joy Brock developed this course in collaboration with . Check out Joy’s channel: 🍬 Sign up for the RealToughCandy newsletter and get a free ebook plus coding challenges, exclusive promo codes and more delivered directly to your inbox. ➡️ ⭐️ Code Samples ⭐️ 🔗 🔗 🔗 🔗 🔗 ⭐️ Course Contents ⭐️ ⌨️ (0:00:00) Intro & course overview ⌨️ (0:07:07) Factorials refresher ⌨️ (0:10:04) CODING CHALLENGE: Factorial program using iteration, recursion ⌨️ (0:14:57) What is a permutation? ⌨️ (0:16:34) CODING CHALLENGE: Recursive permutation ⌨️ (0:20:13) Iterative permutation example ⌨️ (0:22:17) 8/N queens problem: theory & explanation ⌨️ (0:23:57) Real world example of permutations ⌨️ (0:24:49) Lesson recap ⌨️ (0:26:11) What are data structures? ⌨️ (0:27:53) What is a one-dimensional array? ⌨️ (0:29:01) Search & sort ⌨️ (0:30:39) CODING CHALLENGE: Linear search ⌨️ (0:31:00) Binary search ⌨️ (0:32:06) CODING CHALLENGE: Iterative binary search ⌨️ (0:33:31) Coding a recursive binary search ⌨️ (0:34:47) Bubble sort ⌨️ (0:36:42) CODING CHALLENGE: Bubble sort ⌨️ (0:38:02) Insertion sort ⌨️ (0:39:24) CODING CHALLENGE: Insertion sort ⌨️ (0:40:36) Linked lists ⌨️ (0:44:01) CODING CHALLENGE: Linked list (traverse, search, add, delete, header, nodes, tail) ⌨️ (0:52:12) Hash tables ⌨️ (0:56:27) Lesson recap ⌨️ (0:57:42) Divide & conquer algorithm paradigm: uses, benefits and more ⌨️ (1:00:43) Merge sort ⌨️ (1:02:48) CODING CHALLENGE: An efficient merge sort ⌨️ (1:05:48) Getting judged mercilessly on LeetCode ⌨️ (1:06:47) Getting Python to do the work for us with sorted() ⌨️ (1:07:33) Matrix multiplication ⌨️ (1:10:06) CODING CHALLENGE: Matrix multiplication ⌨️ (1:11:20) Strassen algorithm ⌨️ (1:14:45) CODING CHALLENGE: Strassen algorithm ⌨️ (1:16:27) Lesson recap ⌨️ (1:17:21) What is a greedy algorithm? ⌨️ (1:19:20) Assign mice to holes conceptual overview ⌨️ (1:21:45) CODING CHALLENGE: Assign mice to holes ⌨️ (1:23:10) Fractional knapsack ⌨️ (1:23:36) Understanding the fractional knapsack problem with a (light-hearted) dystopian apocalypse example ⌨️ (1:25:54) Coding challenge prep ⌨️ (1:27:13) CODING CHALLENGE: Fractional knapsack ⌨️ (1:31:49) Egyptians fractions ⌨️ (1:34:03) CODING CHALLENGE: Egyptian fractions ⌨️ (1:37:06) Lesson recap ⌨️ (1:38:15) What is dynamic programming (also called DP)? ⌨️ (1:41:55) What is the principle of optimality? ⌨️ (1:42:20) The 3-step process to solving a problem with optimal substructure ⌨️ (1:43:55) Introduction to “ugly numbers” ⌨️ (1:47:19) CODING CHALLENGE: Ugly numbers ⌨️ (1:51:41) Traveling salesman problem (TSP) ⌨️ (1:55:49) CODING CHALLENGE: Traveling salesman problem ⌨️ (1:59:52) Palindromic matrix paths ⌨️ (2:03:11) CODING CHALLENGE: Palindromic matrix paths ⌨️ (2:08:37) Lesson recap ⌨️ (2:10:03) Course wrap up (and the importance of coding every day) 🎉 Thanks to our Champion and Sponsor supporters: 👾 Raymond Odero 👾 Agustín Kussrow 👾 aldo ferretti 👾 Otis Morgan 👾 DeezMaster -- Learn to code for free and get a developer job: Read hundreds of articles on programming:
