The aim of this course is to provide an introduction to mathematical modeling of computational problems. It is an undergraduate course. It covers topics such as the common algorithms, algorithmic paradigms, and data structures used to solve these problems. See More: https://bit.ly/30oZS1v

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Basic Concepts Of Algorithms
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The aim of this course is to provide an introduction to mathematical modeling of computational
problems. It is an undergraduate …
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HOME CURRICULUM REVIEWS
The aim of this course is to provide an introduction to mathematical modeling of computational
problems. It is an undergraduate course. It covers topics such as the common algorithms,
algorithmic paradigms, and data structures used to solve these problems. The course emphasizes
the relationship between algorithms and programming. In addition to that, it introduces basic
performance measures and analysis techniques for these problems.
Assessment
This course does not involve any written exams. Students need to answer 5 assignment questions to
complete the course, the answers will be in the form of written work in pdf or word. Students can
write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers
are submitted, the tutor will check and assess the work.
Certification
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Course Credit: MIT
Module 01
Introduction to Algorithms 00:10:00
More document distance, mergesort 00:10:00
Airplane scheduling, binary search trees 00:10:00
Balanced binary search trees 00:20:00
Hashing I chaining, hash functions 00:10:00
Hashing II table doubling, Karp-Rabin 00:10:00
Hashing III open addressing 00:10:00
Sorting I heaps 00:10:00
Sorting II heaps 00:15:00
Sorting III lower bounds, linear-time sorting 00:10:00
Sorting IV stable sorting, radix sort 00:10:00
Searching I graph search, representations, and applications 00:20:00
Module 02
Searching II breadth- rst search and depth- rst search 00:10:00
Searching III topological sort and NP-completeness 00:10:00
COURSE CURRICULUM

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Shortest paths I intro 00:15:00
Shortest paths II Bellman-Ford 00:10:00
Shortest paths III Dijkstra 00:10:00
Shortest paths IV Dijkstra speedups 00:10:00
Dynamic programming I memoization, Fibonacci, Crazy Eights, guessing 00:10:00
Dynamic programming II longest common subsequence, parent pointers 00:10:00
Dynamic programming III text justi cation, parenthesization, knapsack,
pseudopolynomial time, Tetris training
00:10:00
Dynamic programming IV piano ngering, structural DP (trees), vertex
cover, dominating set, and beyond
00:10:00
Numerics I 00:10:00
Numerics II 00:10:00
Beyond 6.006 follow-on classes, geometric folding algorithms 00:05:00
Assessment
Submit Your Assignment 00:00:00
Certi cation 00:00:00
COURSE REVIEWS

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