Advanced Algorithms Analysis and Design (V-U)

• Introduction (V-U)
• Mathematical Tools (V-U)
• Logic and Proving Techniques (V-U)
• Proofs, Validation, Verification (V-U)
• Strong Math Induction (V-U)
• Fibonacci Sequences (V-U)
• Recurrence Relations: Mathematical Models, Analysis Techniques (V-U)
• Recurrence Relations: Algorithms Design and Analysis Techniques (V-U)
• Further Techniques Solving Recurrence Relations (V-U)
• Time Complexity Measuring Notations (V-U)
• Relations over Asymptotic Notations (V-U)
• Brute Force Approach: Introduction, Starting with Primality, Sorting Sequence of numbers (V-U)
• Designing Algorithms using Brute Force and Divide & Conquer Approaches (V-U)
• Designing Algorithms using Divide & Conquer Approaches (Cont.) (V-U)
• Dynamic Programming for Solving Optimization Problems: Chain Matrix Multiplication Problem (V-U)
• Chain Matrix Multiplication Problem using Dynamic Programming (Cont.) (V-U)
• 2-Line Assembly Scheduling Problem, n-Line Assembly Scheduling Problem (V-U)
• 0-1 Knapsack Problem using Dynamic Programming (V-U)
• 0-1 Knapsack Problem's Algorithm using Dynamic Programming, Optimal Weight Triangulation (V-U)
• Optimal Weight Triangulation using Dynamic Programming (V-U)
• Review Lectures 1-21 (V-U)
• Longest Common Subsequence, Optimal Binary Search Trees (V-U)
• Dynamic Programming: Optimal Binary Search Trees (Cont.) , Greedy Algorithms (V-U)
• Greedy Algorithms: Activity Selection Algorithm, Fractional Knapsack, Coin Change Making (V-U)
• Greedy Algorithms: Huffman Coding (V-U)