LeetCode 207: Course Schedule with DFS and Graphs

✅ Day 54 of 100 Days LeetCode Challenge Problem: 🔹 #728 – Self Dividing Numbers 🔗 https://lnkd.in/gxraQJ82 Learning Journey: 🔹 Today’s problem focused on identifying numbers that are divisible by each of their digits. 🔹 For every number in the given range, I extracted its digits and checked divisibility conditions. 🔹 Any number containing zero was immediately rejected since division by zero is invalid. 🔹 Valid numbers were collected into the final result list. Concepts Used: 🔹 Digit Extraction 🔹 Modulo Arithmetic 🔹 Iterative Checking 🔹 Conditional Filtering Key Insight: 🔹 Breaking numbers into digits simplifies many number-theory problems. 🔹 Early elimination (like handling zeros) improves efficiency. 🔹 Clear validation logic makes implementation straightforward and readable. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 42 of 100 Days LeetCode Challenge Problem: 🔹 #204 – Count Primes 🔗 https://lnkd.in/gjsy54cm Learning Journey: 🔹 Today’s problem focused on counting the number of prime numbers less than a given integer. 🔹 I used the Sieve of Eratosthenes, an efficient algorithm for generating primes by iteratively marking multiples as non-prime. 🔹 Starting from 2, each prime eliminates its multiples, reducing unnecessary checks. 🔹 The remaining true values represent prime numbers. Concepts Used: 🔹 Sieve of Eratosthenes 🔹 Number Theory 🔹 Array Marking Technique 🔹 Optimization Key Insight: 🔹 Instead of checking each number individually, eliminating multiples significantly improves efficiency. 🔹 Starting from i² avoids redundant work because smaller multiples were already handled. 🔹 Preprocessing techniques like sieves are powerful for number-based problems. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 40 of 100 Days LeetCode Challenge Problem: 🔹 #1200 – Minimum Absolute Difference 🔗 https://lnkd.in/gdXZxeGh Learning Journey: 🔹 Today’s problem focused on finding all pairs of elements with the minimum absolute difference in an array. 🔹 I first sorted the array so that the smallest differences would appear between adjacent elements. 🔹 By scanning the sorted list once, I tracked the minimum difference and collected all valid pairs. 🔹 This approach avoids unnecessary comparisons and improves efficiency. Concepts Used: 🔹 Sorting 🔹 Greedy Scanning 🔹 Array Traversal 🔹 Optimization Key Insight: 🔹 Sorting simplifies many comparison-based problems. 🔹 Minimum differences in a sorted array will always occur between neighboring elements. 🔹 Maintaining a running minimum helps build the result efficiently in one pass. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 55 of 100 Days LeetCode Challenge Problem: 🔹 #55 – Jump Game 🔗 https://lnkd.in/gnUUqSxm Learning Journey: 🔹 Today’s problem focused on determining whether we can reach the last index of an array given maximum jump lengths at each position. 🔹 I used a greedy approach, tracking the maximum reachable index while traversing the array. 🔹 If at any point the current index exceeds the maximum reachable position, it means the end cannot be reached. 🔹 Otherwise, I continuously update the furthest reachable index. Concepts Used: 🔹 Greedy Algorithm 🔹 Array Traversal 🔹 Reachability Tracking 🔹 Optimization Strategy Key Insight: 🔹 Instead of exploring all paths, tracking the furthest reachable index is sufficient. 🔹 Greedy decisions at each step can guarantee a global solution in certain problems. 🔹 Efficient state tracking reduces the need for dynamic programming. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 57 of 100 Days LeetCode Challenge Problem: 🔹 #1404 – Number of Steps to Reduce a Number in Binary Representation to One 🔗 https://lnkd.in/ggb5GXaW Learning Journey: 🔹 Today’s problem focused on reducing a binary number to 1 using specific rules. 🔹 If the number is even, divide it by 2. If it is odd, add 1. 🔹 I converted the binary string to an integer, applied the operation, and converted it back to binary after each step. 🔹 The process continued until the value became "1", counting the total operations. Concepts Used: 🔹 Binary Representation 🔹 Bit Manipulation Concepts 🔹 Simulation 🔹 Conditional Logic Key Insight: 🔹 Binary problems often map directly to parity checks (even vs odd). 🔹 Simulation is straightforward but understanding bit behavior can lead to optimized solutions. 🔹 Recognizing patterns in binary transitions improves problem-solving efficiency. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 47 of 100 Days LeetCode Challenge Problem: 🔹 #152 – Maximum Product Subarray 🔗 https://lnkd.in/gcKQWrHz Learning Journey: 🔹 Today’s problem focused on finding the maximum product of a contiguous subarray. 🔹 Unlike sum-based problems, negative numbers can flip the result, so I tracked both maximum and minimum products at each step. 🔹 Whenever a negative number appeared, I swapped the current max and min to maintain correctness. 🔹 This allowed me to dynamically update the best possible product while traversing the array once. Concepts Used: 🔹 Dynamic Programming 🔹 Kadane-like Optimization 🔹 Greedy State Tracking 🔹 Array Traversal Key Insight: 🔹 Keeping track of both maximum and minimum products is essential due to sign changes. 🔹 Negative numbers can turn the smallest product into the largest. 🔹 Maintaining rolling states leads to an efficient O(n) solution. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

𝗜𝗳 𝘆𝗼𝘂 𝘄𝗮𝗻𝘁 𝘁𝗼 𝗹𝗲𝗮𝗿𝗻 𝗣𝘆𝘁𝗵𝗼𝗻 — 𝘁𝗵𝗶𝘀 𝗶𝘀 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗯𝗲𝘀𝘁 𝗿𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝗼𝗻 𝘁𝗵𝗲 𝗶𝗻𝘁𝗲𝗿𝗻𝗲𝘁. 📖 "𝗧𝗵𝗶𝗻𝗸 𝗣𝘆𝘁𝗵𝗼𝗻" by Allen Downey. This is the book every beginner wished existed when they were starting out. It doesn't just teach you syntax — it teaches you how to think like a programmer. Concepts are broken down in a way that actually makes sense, with a focus on problem-solving over memorization. The best part? It's 𝗰𝗼𝗺𝗽𝗹𝗲𝘁𝗲𝗹𝘆 𝗳𝗿𝗲𝗲. No paywalls. No sign-ups. Just open it and start learning. 🔗 https://lnkd.in/gsmPuymX Whether you're an absolute beginner or brushing up on the fundamentals — grab it, open your terminal, and start experimenting. That's where the real learning happens. What's a resource that changed how you learned to code? Drop it in the comments 👇 #Python #LearnToCode #100DaysOfCode #Programming #Tech #DataScience #Developer #CodingTips

✅ Day 39 of 100 Days LeetCode Challenge Problem: 🔹 #114 – Flatten Binary Tree to Linked List 🔗 https://lnkd.in/g6xn2K3g Learning Journey: 🔹 Today’s problem focused on transforming a binary tree into a flattened linked list in-place. 🔹 I used an iterative approach, modifying pointers while traversing the tree. 🔹 For each node with a left subtree, I found the rightmost node of that subtree and connected it to the current node’s right subtree. 🔹 Then, I moved the left subtree to the right and continued traversal. Concepts Used: 🔹 Binary Trees 🔹 Tree Traversal 🔹 Pointer Manipulation 🔹 In-place Modification Key Insight: 🔹 Tree restructuring problems often rely on careful pointer adjustments. 🔹 Finding the predecessor (rightmost node of left subtree) helps preserve traversal order. 🔹 Iterative solutions can avoid recursion and reduce extra space usage. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 38 of 100 Days LeetCode Challenge Problem: 🔹 #323 – Number of Connected Components in an Undirected Graph 🔗 https://lnkd.in/gRVWsWgZ Learning Journey: 🔹 Today’s problem focused on counting connected components in an undirected graph. 🔹 I represented the graph using an adjacency list built from the edge list. 🔹 Using Depth-First Search (DFS), I explored all nodes reachable from a starting node. 🔹 Each new DFS traversal from an unvisited node indicates a new connected component. Concepts Used: 🔹 Depth-First Search (DFS) 🔹 Graph Representation (Adjacency List) 🔹 Connected Components 🔹 Graph Traversal Key Insight: 🔹 Graph problems often reduce to exploring connectivity between nodes. 🔹 Tracking visited nodes prevents redundant traversals. 🔹 Iterative DFS using a stack provides a clean and efficient solution. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

Most beginners learn Tuples wrong. They memorize: - syntax - definitions But tuples are not about syntax they are about designing safer systems. Today, I built a small real-life mini project A Student Record System using tuples. student = ("Hamim", 25, ("Python", "UI/UX", "Framer"), "Bangladesh") Here’s what this taught me: Tuples = immutable → protect critical data Nested tuples = structured grouping Unpacking = clean, readable code Perfect for fixed records & function returns This made one thing clear: Not everything should be a list. Use tuples when data must stay consistent. 💬 Curious question for fellow learners: Where have you used tuples in a real project-not just in tutorials? Let’s learn by building, not memorizing. #Python #LearningInPublic #SoftwareDesign #Programming #BeginnerDeveloper #CleanCode #CSFundamentals