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1 | 1 | # Complete Java + DSA Bootcamp Syllabus
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2 | 2 |
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3 | 3 | ## NOTE:
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4 |
| -- All topics will contain problems from LeetCode Easy to Hard, explained in an easy to understand manner. |
5 |
| -- Complete Custom Implementation of all Data Structures and Algorithms. |
| 4 | +- All topics will contain problems from LeetCode Easy to Hard, explained in an easy-to-understand manner. |
| 5 | +- Complete custom implementation of all Data Structures and Algorithms. |
6 | 6 |
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7 | 7 | ## Lectures
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8 | 8 | - Introduction to Git
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28 | 28 | - Bubble Sort
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29 | 29 | - Count Sort
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30 | 30 | - Radix Sort
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| 31 | + - Cyclic Sort |
31 | 32 | - Searching
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32 | 33 | - Linear Search
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33 | 34 | - Binary Search
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51 | 52 | - Newton's Square Root Method
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52 | 53 | - Number Theory
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53 | 54 | - Euclidean algorithm
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54 |
| - - Advanced Concepts for CP (later in course) |
| 55 | + - Advanced Concepts for CP (later in the course) |
55 | 56 | - Bitwise + DP
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56 | 57 | - Extended Euclidean algorithm
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57 | 58 | - Modulo Properties
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58 | 59 | - Modulo Multiplicative Inverse
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59 | 60 | - Linear Diophantine Equations
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60 |
| - - Fremat's Theorem |
| 61 | + - Fermat’s Theorem |
61 | 62 | - Wilson's Theorem
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62 | 63 | - Lucas Theorem
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63 | 64 | - Chinese Remainder Theorem
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68 | 69 | - Shadowing
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69 | 70 | - Variable Length Arguments
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70 | 71 | - (more content in OOP such as overloading etc)
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71 |
| -- Space and Time Complexity Analysis |
72 |
| - - Introduction |
73 |
| - - Comparion of various cases |
74 |
| - - Solving Linear Recurrence Relations |
75 |
| - - Solving Divide and Conquer Recurrence Relations |
76 |
| - - Big-O, Big-Omega, Big-Theta Notations |
77 |
| - - Get equation of any relation easily - best and easiest approach |
78 |
| - - Complexity discussion of all the problems we do |
79 |
| - - Space Complexity |
80 |
| - - Memory Allocation of various languages |
81 |
| - - NP Completeness and Hardness |
| 72 | + |
82 | 73 | - Recursion
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83 | 74 | - Introduction
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84 | 75 | - Why recursion?
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89 | 80 | - Sorting:
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90 | 81 | - Merge Sort
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91 | 82 | - Quick Sort
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92 |
| - - Cyclic Sort |
93 | 83 | - Backtracking
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94 | 84 | - Sudoku Solver
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95 | 85 | - N-Queens
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99 | 89 | - Recursion Array Problems
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100 | 90 | - Recursion Pattern Problems
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101 | 91 | - Subset Questions
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| 92 | +- Space and Time Complexity Analysis |
| 93 | + - Introduction |
| 94 | + - Comparisons of various cases |
| 95 | + - Solving Linear Recurrence Relations |
| 96 | + - Solving Divide and Conquer Recurrence Relations |
| 97 | + - Big-O, Big-Omega, Big-Theta Notations |
| 98 | + - Get equation of any relation easily - best and easiest approach |
| 99 | + - Complexity discussion of all the problems we do |
| 100 | + - Space Complexity |
| 101 | + - Memory Allocation of various languages |
| 102 | + - NP-Completeness and Hardness |
102 | 103 | - Object Oriented Programming
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103 | 104 | - Introduction
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104 | 105 | - Classes & its instances
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128 | 129 | - Fast and slow pointer
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129 | 130 | - Cycle Detection
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130 | 131 | - Single and Doubly LinkedList
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131 |
| - - Reversalof LinekdList |
| 132 | + - Reversal of LinkedList |
132 | 133 | - Dynamic Programming
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133 | 134 | - Introduction
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134 | 135 | - Recursion + Recursion DP + Iteration + Iteration Space Optimized
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135 | 136 | - Complexity Analysis
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136 | 137 | - 0/1 Knapsack
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137 | 138 | - Subset Questions
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138 | 139 | - Unbounded Knapsack
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139 |
| - - Subseq questions |
| 140 | + - Subsequence questions |
140 | 141 | - String DP
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141 | 142 | - Trees
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142 | 143 | - Introduction
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154 | 155 | - Priority Queue
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155 | 156 | - Two Heaps Method
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156 | 157 | - k-way merge
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157 |
| - - top k elements |
158 |
| - - interval problems |
159 |
| -- Hashmaps |
| 158 | + - Top k elements |
| 159 | + - Interval problems |
| 160 | +- HashMap |
160 | 161 | - Introduction
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161 | 162 | - Theory - how it works
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162 | 163 | - Comparisons of various forms
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178 | 179 | - Dijkstra’s shortest path algorithm
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179 | 180 | - Topological Sort
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180 | 181 | - Bellman ford
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181 |
| - - A* pathfinding Algorithm |
| 182 | + - A* pathfinding Algorithm |
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