Course Curriculum
Total learning: 59 lessons Time: 100 weeks
- Asymptotic Notations : Introduction.Lecture1.1
- Big Oh (O) : Example – 1Lecture1.2
- Big Oh (O) : Example – 2Lecture1.3
- Big Oh (O) : Example – 3Lecture1.4
- Big Oh (O) : Multiplication and AdditionLecture1.5
- Big Omega (Ω)Lecture1.6
- Theta (Θ)Lecture1.7
- PropertiesLecture1.8
- Example : 4Lecture1.9
- Examples CopyLecture1.10
- Introduction CopyLecture2.1
- Time Complexity Calculation for Simple Loops – 1Lecture2.2
- Time Complexity Calculation for Simple Loops – 2Lecture2.3
- Time Complexity Calculation for Nested Loops – 1Lecture2.4
- Time Complexity Calculation for Nested Loops – 2Lecture2.5
- Master Theorem Introduction.Lecture3.1
- Master Theorem Formula discussion.Lecture3.2
- Master Theorem Examples – 1Lecture3.3
- Master Theorem Examples – 2Lecture3.4
- Spanning Trees Introduction.Lecture4.1
- Spanning Trees Properties Continuation.Lecture4.2
- Minimum Spanning Trees Definition and Algorithms IntroductionLecture4.3
- Krushkal’s Algorithm for finding Minimum Spanning Trees.Lecture4.4
- Krushkal’s Algorithm for finding Minimum Spanning Trees ContinuationLecture4.5
- Krushkal’s Algorithm for finding Minimum Spanning Trees – Time Complexity.Lecture4.6
- Prim’s Algorithm for finding Minimum Spanning Tree and Time Complexity.Lecture4.7
- 1. Bubble Sort : Understanding ExampleLecture5.1
- 1. Bubble Sort : Time ComplexityLecture5.2
- 1. Bubble Sort : AlgorithmLecture5.3
- 1. Bubble Sort : Reducing Time ComplexityLecture5.4
- Code : Bubble SortLecture5.5
- 2. Insertion Sort : Understanding ExampleLecture5.6
- 2. Insertion Sort : AlgorithmLecture5.7
- 2. Insertion Sort : Time ComplexityLecture5.8
- Code : Insertion SortLecture5.9
- 3. Selection Sort : Understanding ExampleLecture5.10
- 3. Selection Sort : AlgorithmLecture5.11
- 3. Selection Sort : Time ComplexityLecture5.12
- CodeLecture5.13
- Heap Sort : Understanding with ExampleLecture5.14
- Heap Sort : Time ComplexityLecture5.15
- Linear SearchLecture6.1
- Code : Linear SearchLecture6.2
- Binary Search : Understanding with ExampleLecture6.3
- Binary Search : Iterative and Recursive AlgorithmsLecture6.4
- Code : Binary Search – IterativeLecture6.5
- Code : Binary Search – RecursiveLecture6.6
- Matrix Chain MultiplicationLecture7.1
- Job Sequencing Problem : TheoryLecture8.1
- Job Sequencing Problem : Example 1Lecture8.2
- Job Sequencing Problem : Example 2Lecture8.3
- Knapsack Problem : TheoryLecture8.4
- Knapsack Problem : Example – Greedy about Weight, Profit and Unit Cost.Lecture8.5
- Optimal Merge Pattern : TheoryLecture8.6
- Optimal Merge Pattern : ExampleLecture8.7
- Dynamic Programming : IntroductionLecture8.8
- Multistage GraphLecture8.9
- Travelling Salesperson Problem CopLecture8.10
- All Pairs Shortest Path ProblemLecture8.11
Aymptotic Notations 10
Time Complexity 5
Master Theorem 4
Spanning Trees 7
Sorting Algorithms 15
Searching Algorithms 6
Matrix Chain Multiplication 1
Greedy Method 11
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