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Complete index of every page on Algorithms in 60 Days: all 60 algorithm lessons, blog articles, the Python primer, and key site pages.
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Algorithm Days
- Day 1: Introduction to Algorithms
- Day 2: Algorithmic Thinking and Pseudocode
- Day 3: Introduction to Time Complexity
- Day 4: Introduction to Arrays
- Day 5: Multi-Dimensional Arrays and Sorting Algorithms
- Day 6: Advanced Sorting Algorithms - Insertion Sort and Merge Sort
- Day 7: Introduction to Linked Lists
- Day 8: Singly Linked Lists - Implementation and Basic Operations
- Day 9: Doubly Linked Lists - Implementation and Comparison
- Day 10: Advanced Linked List Operations and Problems
- Day 11: Introduction to Stacks
- Day 12: Introduction to Queues
- Day 13: Introduction to Trees
- Day 14: Binary Trees
- Day 15: Binary Search Trees
- Day 16: Tree Traversals
- Day 17: Heaps and Priority Queues
- Day 18: Introduction to Graphs
- Day 19: Graph Representations
- Day 20: Graph Traversals - BFS and DFS
- Day 21: Shortest Path Algorithms
- Day 22: Minimum Spanning Trees
- Day 23: Hash Tables
- Day 24: Sets and Their Applications
- Day 25: Binary Search and Its Variations
- Day 26: Quicksort Algorithm
- Day 27: Mergesort Algorithm
- Day 28: Heapsort Algorithm
- Day 29: Comparison of Sorting Algorithms
- Day 30: Introduction to Dynamic Programming
- Day 31: Fibonacci Sequence and Dynamic Programming
- Day 32: Longest Common Subsequence
- Day 33: The Knapsack Problem
- Day 34: Matrix Chain Multiplication
- Day 35: Longest Increasing Subsequence
- Day 36: Edit Distance Problem
- Day 37: Coin Change Problem
- Day 38: Rod Cutting Problem
- Day 39: Palindrome Partitioning
- Day 40: Introduction to Greedy Algorithms
- Day 41: Activity Selection Problem
- Day 42: Huffman Coding
- Day 43: Dijkstra's Algorithm
- Day 44: Prim's Algorithm
- Day 45: Kruskal's Algorithm
- Day 46: Floyd-Warshall Algorithm
- Day 47: Bellman-Ford Algorithm
- Day 48: Introduction to Backtracking
- Day 49: N-Queens Problem
- Day 50: Sudoku Solver
- Day 51: Hamiltonian Cycle
- Day 52: Graph Coloring
- Day 53: Bit Manipulation Techniques
- Day 54: Power Set
- Day 55: Counting Bits
- Day 56: String Algorithms - KMP
- Day 57: Rabin-Karp Algorithm
- Day 58: Tries
- Day 59: Advanced Tree Structures
- Day 60: Competitive Programming Techniques and Wrap-up
Topics
- Dynamic Programming for Coding Interviews
- Array Interview Questions and Algorithms
- Linked Lists: A Study Guide
- Stacks and Queues: A Study Guide
- Big-O Cheat Sheet: Time & Space Complexity Reference
- Trees: A Study Guide
- Big-O Quiz: Guess the Time Complexity
- Heaps: A Study Guide
- Binary Search Visualizer: Watch It Narrow the Range
- Hashing: A Study Guide
- Greedy Algorithms: A Study Guide
- Backtracking: A Study Guide
- Strings: A Study Guide
- Graph Algorithms You Must Know for FAANG Interviews
Sorting Visualizations
Study Plans
Blog
- NeetCode vs Blind 75 vs 60-Day Plan: Which Should You Use?
- Meta (Facebook) Interview Prep: Coding Rounds Explained
- Binary Tree Interview Questions: Patterns, Tips, and Solutions
- Is LeetCode Premium Worth It? An Honest Look at Alternatives
- How to Prepare for the Google Coding Interview (2026 Guide)
- Amazon Coding Interview Prep: What They Actually Test in 2026
- 10 Dynamic Programming Patterns Every FAANG Candidate Must Know
- The Best FAANG Interview Prep Resources in 2026 (Free + Paid)
- Bit Manipulation Tricks for Coding Interviews
- The Data Structures Cheatsheet: Time & Space Complexity for Every Structure You Need
- Hash Maps and Sets: The Most Underrated FAANG Topic
- Binary Search: Not Just for Sorted Arrays
- Tries Explained Simply (With Real Interview Problems)
- Recursion for Interviews: Think Before You Code
- The Sliding Window Technique: Explained with 5 Interview Problems
- Two Pointer Technique: When to Use It and 6 Problems Solved
- How Long Does It Take to Get a FAANG Offer?
- Backtracking Explained: N-Queens to Subsets
- API Analytics: Measuring Performance and Usage for Continuous Improvement
- Deploying Your API: Strategies for Secure, Scalable, and Reliable API Deployment
- API Versioning Strategies: Managing Backward Compatibility and Seamless Upgrades
- The Ultimate API Security Checklist: Because Sleep is Overrated
- Comprehensive API Testing: Strategies for Ensuring Quality and Reliability
- Building a Resilient API: Handling Failures and Implementing Retries
- API Security Checklist: Essential Strategies for API Protection
- API Security Best Practices: Protecting Sensitive Data and Preventing Attacks
- API Monitoring and Logging: Tracking and Troubleshooting in Real Time
- Optimizing API Performance: Caching, Rate Limiting, and Response Time Improvements
- Advanced API Security: Scopes, Roles, and Permissions
- Working with APIs Using JWT (JSON Web Tokens)
- Rate Limiting, Error Handling, and Best Practices for API Design
- OAuth and API Authentication: Accessing Secure APIs
- Advanced API Usage: Pagination, Filtering, and Handling Large Datasets
- Working with APIs: Fetching Data from External Sources
- File I/O: Reading and Writing Files in Python
- Error Handling and Exceptions in Python
- Hashing and Hash Functions: Efficient Data Retrieval
- Introduction to Merge Sort and Time Complexity
- Introduction to Searching and Sorting Algorithms
- Practical Applications of Dictionaries and Sets
- Dictionaries and Sets: Efficient Data Retrieval
- Lists and Arrays: Storing Collections of Data
- Modules and Importing: Reusing Code Efficiently
- Advanced Functions: Default Arguments, Lambda Functions, and Scope
- Introduction to Functions: Organizing Code with Functions
- Loops in Programming: Repeating with For and While
- Control Structures: Mastering Program Flow
- Setting Up Your Development Environment: The First Step in Your Coding Journey
- Arrays and Lists: Mastering Collections in Python
- Strings and String Manipulation: Mastering Text Processing in Python
- Boolean and Character Data Types: Mastering Logic and Text in Programming
- Numeric Data Types: Mastering Integers and Floats in Programming
- Introduction to Programming and Variables: Your First Step in Coding
- Question: Matrix Multiplication Why We Need Nested Loops
Python Primer
- Python for DSA: The Primer Track
- Lists and Tuples in Python
- Dictionaries and Sets in Python
- Strings in Python
- Functions and Recursion in Python
- Classes and OOP in Python
- Iterators and Comprehensions in Python
- Control Flow, Loops, and Iteration Patterns
- Built-in Data Structures Deep Dive
- Functions, Arguments, Scope, and Closures
- OOP for DSA
- Python Interview Idioms
- Python Standard Library for DSA
- Complexity and Performance of Python Operations
- Input Parsing, Testing, and Debugging for Challenges
- Python Basics Plan