Ace FAANG Interviews: Dynamic Programming for Senior Engineers

Unit 1: What is Dynamic Programming?

Unit 2: DP vs. Other Algorithmic Approaches

Unit 3: Overlapping Subproblems and Optimal Substructure

Unit 4: DP in Action

Unit 1: Recursion Refresher

Unit 2: Memoization: Top-Down DP

Unit 3: Fibonacci with Memoization

Unit 1: Understanding Tabulation

Unit 2: Fibonacci with Tabulation

Unit 3: Tabulation Trade-offs

Unit 1: Identifying DP Problems

Unit 2: Formulating Recurrence Relations

Unit 3: Base Cases and Boundary Conditions

Unit 4: Implementing DP Solutions

Unit 1: Recursive Fibonacci

Unit 2: Memoization

Unit 3: Tabulation

Unit 4: Space Optimization

Unit 5: Comparison and Conclusion

Unit 1: Understanding the 0/1 Knapsack Problem

Unit 2: Formulating the Recurrence Relation

Unit 3: Implementing the Solutions

Unit 4: Analyzing Complexity

Unit 1: Understanding Unbounded Knapsack

Unit 2: Memoization and Tabulation

Unit 3: Optimization and Applications

Unit 1: Understanding the Minimum Coins Problem

Unit 2: Memoization Approach

Unit 3: Tabulation Approach

Unit 4: Complexity and Optimizations

Unit 1: Understanding the Number of Ways Coin Change Problem

Unit 2: Memoization for Coin Change

Unit 3: Tabulation for Coin Change

Unit 1: LCS Fundamentals

Unit 2: Memoization for LCS

Unit 3: Tabulation for LCS

Unit 4: Reconstruction and Wrap-up

Unit 1: Understanding Edit Distance

Unit 2: Formulating the Recurrence Relation

Unit 3: Memoization and Tabulation

Unit 4: Code Optimization and Applications

Unit 1: Understanding Matrix Chain Multiplication

Unit 2: Dynamic Programming Approach

Unit 3: Implementation and Optimization

Unit 1: Graphs and DP Intro

Unit 2: Bellman-Ford Algorithm

Unit 3: Floyd-Warshall Algorithm

Unit 4: DP and Shortest Paths

Unit 1: Bellman-Ford Fundamentals

Unit 2: Implementation and Negative Cycle Detection

Unit 3: Complexity Analysis and Applications

Unit 1: Understanding Floyd-Warshall

Unit 2: Implementing the Algorithm

Unit 3: Negative Cycle Detection & Analysis

Unit 1: Subsequence Fundamentals

Unit 2: Longest Increasing Subsequence (LIS)

Unit 3: Longest Palindromic Subsequence (LPS)

Unit 4: Putting It All Together

Unit 1: LIS Fundamentals

Unit 2: DP Solutions for LIS

Unit 3: Optimizing LIS

Unit 1: LPS Fundamentals

Unit 2: DP Approaches to LPS

Unit 3: LPS and LCS

Unit 1: Longest Common Substring

Unit 2: Minimum Window Substring

Unit 3: Substring Patterns and Applications

Unit 1: Understanding the Basics

Unit 2: DP Formulation and Implementation

Unit 3: Optimization and Advanced Concepts

Unit 1: Understanding the Problem

Unit 2: Applying Sliding Window to MWS

Unit 3: Putting It All Together

Unit 1: Palindrome Fundamentals

Unit 2: Palindrome Partitioning

Unit 3: Longest Palindromic Substring

Unit 4: LPS vs. LCS

Unit 1: Understanding Palindromes

Unit 2: Palindrome Partitioning Problem

Unit 3: Dynamic Programming Solution

Unit 4: Variations and Optimizations

Unit 5: Practice and Applications

Unit 1: Understanding Palindromes

Unit 2: DP Formulation and Implementation

Unit 3: Optimizations and Comparisons

Unit 1: Fundamentals of Complexity Analysis

Unit 2: Complexity of Memoized DP Solutions

Unit 3: Complexity of Tabulated DP Solutions

Unit 4: Optimization Opportunities

Unit 1: Understanding Space Complexity

Unit 2: Rolling Arrays: The Basics

Unit 3: Rolling Arrays: Examples

Unit 4: Advanced Rolling Array Techniques

Unit 5: Limitations and Considerations

Unit 1: Introduction to State Compression

Unit 2: Applying State Compression

Unit 3: Advanced State Compression Techniques

Unit 1: Bitmasking Fundamentals

Unit 2: Bit Manipulation Techniques

Unit 3: Bitmasking in DP

Unit 1: TSP Introduction and Basics

Unit 2: Bitmasking for TSP

Unit 3: DP Formulation for TSP

Unit 4: Implementation and Analysis

Unit 1: Introduction to Tree DP

Unit 2: Basic Tree DP Problems

Unit 3: Maximum Independent Set

Unit 1: Understanding Independent Sets

Unit 2: Tree DP Fundamentals

Unit 3: Implementing the Solution

Unit 4: Complexity Analysis and Optimizations

Unit 1: Digit DP Fundamentals

Unit 2: Digit DP Problem Solving

Unit 3: Advanced Digit DP Techniques

Unit 1: Digit DP Fundamentals

Unit 2: Implementing Digit DP

Unit 3: Advanced Digit DP Techniques

Unit 1: Identifying DP Problems

Unit 2: Formulating Recurrence Relations

Unit 3: Problem-Solving Strategies

Unit 1: Understanding the DP Landscape

Unit 2: Implementation Strategies

Unit 3: Putting It All Together

Unit 1: Introduction to Real-World DP

Unit 2: DP in Computer Science and Engineering

Unit 3: Limitations and Considerations

Unit 1: Introduction to Game Theory

Unit 2: DP and Minimax

Unit 3: Game Theory Problems

Unit 1: Understanding Minimax

Unit 2: Implementing Minimax

Unit 3: Advanced Concepts and Limitations

Unit 1: Intro to Combinatorial Optimization with DP

Unit 2: Cutting Stock Problem

Unit 3: Bin Packing Problem

Unit 1: Understanding the Cutting Stock Problem

Unit 2: Formulating CSP as a DP Problem

Unit 3: Implementing DP Solutions for CSP

Unit 4: Analyzing Complexity and Advanced Topics

Unit 1: Introduction to Bin Packing

Unit 2: Formulating BPP as a DP Problem

Unit 3: Implementing DP Solutions

Unit 4: Variations and Advanced Topics

Unit 1: Introduction to Advanced Data Structures for DP

Unit 2: Segment Trees for DP Optimization

Unit 3: Binary Indexed Trees (Fenwick Trees) for DP Optimization

Unit 4: Other Advanced Data Structures and Conclusion

Unit 1: Introduction to Segment Trees

Unit 2: Implementing Segment Trees

Unit 3: Advanced Segment Tree Concepts

Unit 1: Introduction to Binary Indexed Trees

Unit 2: Implementing Binary Indexed Trees

Unit 3: BITs and Dynamic Programming

Unit 1: Fundamentals Revisited

Unit 2: Simple DP Problems

Unit 3: Knapsack Lite

Unit 1: Medium DP Problems - Part 1

Unit 2: Medium DP Problems - Part 2

Unit 3: Medium DP Problems - Part 3

Unit 1: Hard DP Problems - Part 1

Unit 2: Hard DP Problems - Part 2

Unit 3: Hard DP Problems - Part 3

Unit 1: Essential DP Problems

Unit 2: Intermediate DP Challenges

Unit 3: Advanced DP Strategies

Unit 1: Mock Interview Prep

Unit 2: Mock Interview Sessions

Unit 3: Post-Interview Analysis and Improvement

Unit 1: Wrapping Up Dynamic Programming

Unit 2: Continued Learning and Improvement

Unit 3: Applying DP in the Real World