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take U forward

Dynamic Programming Playlist | Interview Questions | Recursion | Tabulation | Striver | C++ | Java | DSA | Placements

via YouTube Video playlist

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Overview

The playlist aims to teach you Dynamic Programming in depth. The focus of the playlist is to cover all the concepts, and then follow it up with a lot of problems so that the concepts go into your head and stay there.

The focus is on logic, so no matter in which language you code, you can easily convert it into code, as we will be writing the pseudocode while teaching.

You can also find notes in the description of all the videos so that you can easily revise.

In case you have limited time, we will recommend you watch the extracted version of this playlist.

Link: https://www.youtube.com/playlist?list=PLgUwDviBIf0pwFf-BnpkXxs0Ra0eU2sJY

Videos in this playlist 57

  1. Striver's Dynamic Programming Series | The ULTIMATE | The BIGGEST | Teaser #shorts
  2. DP 1. Introduction to Dynamic Programming | Memoization | Tabulation | Space Optimization Techniques
  3. DP 2. Climbing Stairs | Learn How to Write 1D Recurrence Relations
  4. DP 3. Frog Jump | Dynamic Programming | Learn to write 1D DP
  5. DP 4. Frog Jump with K Distance | Lecture 3 Follow Up Question
  6. DP 5. Maximum Sum of Non-Adjacent Elements | House Robber | 1-D | DP on Subsequences
  7. DP 6. House Robber 2 | 1D DP | DP on Subsequences
  8. DP 7. Ninja's Training | MUST WATCH for 2D CONCEPTS 🔥 | Vacation | Atcoder | 2D DP |
  9. DP 8. Grid Unique Paths | Learn Everything about DP on Grids | ALL TECHNIQUES 🔥
  10. DP 9. Unique Paths 2 | DP on Grid with Maze Obstacles
  11. DP 10. Minimum Path Sum in Grid | Asked to me In Microsoft Internship Interview | DP on GRIDS
  12. DP 11. Triangle | Fixed Starting Point and Variable Ending Point | DP on GRIDS
  13. DP 12. Minimum/Maximum Falling Path Sum | Variable Starting and Ending Points | DP on Grids
  14. DP 13. Cherry Pickup II | 3D DP Made Easy | DP On Grids
  15. DP 14. Subset Sum Equals to Target | Identify DP on Subsequences and Ways to Solve them
  16. DP 15. Partition Equal Subset Sum | DP on Subsequences
  17. Dp 16. Partition A Set Into Two Subsets With Minimum Absolute Sum Difference | DP on Subsequences
  18. DP 17. Counts Subsets with Sum K | Dp on Subsequences
  19. DP 18. Count Partitions With Given Difference | Dp on Subsequences
  20. DP 19. 0/1 Knapsack | Recursion to Single Array Space Optimised Approach | DP on Subsequences
  21. DP 20. Minimum Coins | DP on Subsequences | Infinite Supplies Pattern
  22. DP 21. Target Sum | DP on Subsequences
  23. DP 22. Coin Change 2 | Infinite Supply Problems | DP on Subsequences
  24. DP 23. Unbounded Knapsack | 1-D Array Space Optimised Approach
  25. DP 24. Rod Cutting Problem | 1D Array Space Optimised Approach
  26. Dp 25. Longest Common Subsequence | Top Down | Bottom-Up | Space Optimised | DP on Strings
  27. DP 26. Print Longest Common Subsequence | Dp on Strings
  28. DP 27. Longest Common Substring | DP on Strings 🔥
  29. DP 28. Longest Palindromic Subsequence
  30. DP 29. Minimum Insertions to Make String Palindrome
  31. DP 30. Minimum Insertions/Deletions to Convert String A to String B
  32. DP 31. Shortest Common Supersequence | DP on Strings
  33. DP 32. Distinct Subsequences | 1D Array Optimisation Technique 🔥
  34. DP 33. Edit Distance | Recursive to 1D Array Optimised Solution 🔥
  35. DP 34. Wildcard Matching | Recursive to 1D Array Optimisation 🔥
  36. DP 35. Best Time to Buy and Sell Stock | DP on Stocks 🔥
  37. DP 36. Buy and Sell Stock - II | Recursion to Space Optimisation
  38. DP 37. Buy and Sell Stocks III | Recursion to Space Optimisation
  39. DP 38. Buy and Stock Sell IV | Recursion to Space Optimisation
  40. DP 39. Buy and Sell Stocks With Cooldown | Recursion to Space Optimisation
  41. DP 40. Buy and Sell Stocks With Transaction Fee | Recursion to Space Optimisation
  42. DP 41. Longest Increasing Subsequence | Memoization
  43. DP 42. Printing Longest Increasing Subsequence | Tabulation | Algorithm
  44. DP 43. Longest Increasing Subsequence | Binary Search | Intuition
  45. DP 44. Largest Divisible Subset | Longest Increasing Subsequence
  46. DP 45. Longest String Chain | Longest Increasing Subsequence | LIS
  47. DP 46. Longest Bitonic Subsequence | LIS
  48. DP 47. Number of Longest Increasing Subsequences
  49. DP 48. Matrix Chain Multiplication | MCM | Partition DP Starts 🔥
  50. DP 49. Matrix Chain Multiplication | Bottom-Up | Tabulation
  51. DP 50. Minimum Cost to Cut the Stick
  52. DP 51. Burst Balloons | Partition DP | Interactive G-Meet Session Update
  53. DP 52. Evaluate Boolean Expression to True | Partition DP
  54. DP 53. Palindrome Partitioning - II | Front Partition 🔥
  55. DP 54. Partition Array for Maximum Sum | Front Partition 🔥
  56. DP 55. Maximum Rectangle Area with all 1's | DP on Rectangles
  57. DP 56. Count Square Submatrices with All Ones | DP on Rectangles 🔥

Advantages and disadvantages

Advantages

  • Free and complete: every lecture is in the playlist, in order.
  • Watch at 1.5x, skip what you know, rewatch what you don't.
  • The DSA sheet and videos many students follow for placement interviews.
  • 2,019,383 views, so help and notes are easy to find.
  • Completely free.
  • Self-paced: start any time.
  • A clear syllabus (57 videos) you can see before you start.
  • Start watching right away, no sign-up.

Disadvantages

  • No certificate, deadlines or graded work.
  • Quality and depth vary: check that the playlist is finished before you start.
  • Assumes you already know one programming language well.
  • No certificate.
  • No graded assignments or feedback.

Some points apply to every course of this kind; see how we rank.

Free

  • Free: Watch on YouTube, no account needed.
  • Certificate: None. Code or take notes along to make it stick.

take U forward is in Tier 3: good universities, respected companies, nonprofits and well-known teachers of our institution ranking (82/100). The go-to DSA and placement series.

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