Introduction, asymptotic notation, empirical analysis of algorithms, designing algorithms, amortized analysis, brute force algorithms, divide and conquer algorithms, transform and conquer algorithms, space and time trade-offs, dynamic programming, greedy algorithms, advanced data structures, B-trees, Insertion and Deletion from B-trees, graphs and graph algorithms, P, NP, and NP-complete problems. |
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Week |
Subject |
Related Preparation |
1) |
Introduction, asymptotic notation. |
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2) |
Empirical analysis of algorithms, analysis of algorithms, amortized analysis |
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3) |
Recurrences, substitution method, recursion-tree method, master method. |
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4) |
Brute Force Algorithms |
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5) |
Divide and Conquer Algorithms |
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6) |
Merge sort, quicksort, randomized quicksort, binary search |
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7) |
Transform and Conquer Algorithms: Solving systems of linear equations with Gaussian ination elimination, Balanced Search Trees, Heaps and Heapsort, Horner's Rule and Binary Exponentiation
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8) |
Space and Time Trade-offs: Input Enhancement (Counting based sorting, string matching), Prestructuring (Hashing, Hash functions, open addressing).
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9) |
Midterm |
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10) |
Dynamic Programming: Coin-row problem, Knapsack problem, Longest common subsequence. |
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11) |
Dynamic Programming: Knapsack problem, Longest common subsequence. |
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12) |
Greedy Algorithms: Activity selection, Huffman codes, Prim’s algorithm, Kruskal’s Algorithm |
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13) |
Single-source shortest paths: The Bellman-Ford algorithm, Dijkstra's algorithm. |
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14) |
P, NP, and NP-complete problems |
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Course Notes: |
Anany Levitin, The Design and Analysis of Algorithms, Pearson International Third Edition.
Cormen, T. H., Leiserson, C. E., Rivest, R. L. and Stein, C., Introduction to Algorithms (3rd Edition), MIT Press, 2009.
Sanjoy Dasgupta , Christos Papadimitriou, Umesh Vazirani, Algorithms, McGraw-Hill Education.
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References: |
Yok - None |
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Program Outcomes |
Level of Contribution |
1) |
Have sufficient background in mathematics, science and artificial intelligence engineering. |
5 |
2) |
Use theoretical and applied knowledge in the fields of mathematics, science and artificial intelligence engineering together for engineering solutions. |
5 |
3) |
Identify, define, formulate and solve engineering problems, select and apply appropriate analytical methods and modeling techniques for this purpose. |
5 |
4) |
Analyse a system, system component or process and design it under realistic constraints to meet desired requirements; apply modern design methods in this direction. |
5 |
5) |
Select and use modern techniques and tools necessary for engineering applications. |
5 |
6) |
Design and conduct experiments, collect data, and analyse and interpret results. |
5 |
7) |
Work effectively both as an individual and as a multi-disciplinary team member. |
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8) |
Access information via conducting literature research, using databases and other resources |
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9) |
Follow the developments in science and technology and constantly update themself with an awareness of the necessity of lifelong learning. |
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10) |
Use information and communication technologies together with computer software with at least the European Computer License Advanced Level required by their field. |
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11) |
Communicate effectively, both verbal and written; know a foreign language at least at the European Language Portfolio B1 General Level. |
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12) |
Have an awareness of the universal and social impacts of engineering solutions and applications; know about entrepreneurship and innovation; and have an awareness of the problems of the age. |
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13) |
Have a sense of professional and ethical responsibility. |
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14) |
Have an awareness of project management, workplace practices, employee health, environment and work safety; know the legal consequences of engineering practices. |
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