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Algorithms Design and Analysis Diploma ( 9 REVIEWS )
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The algorithm is the set of rules that are followed by calculations and processes by computers. Learning how to design …
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1 YEAR LEVEL 3 - DIPLOMA COURSE BADGE COURSE CERTIFICATE
96
NUMBER OF UNITS NUMBER OF QUIZZES
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17 HOURS, 8 MINUTES
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The algorithm is the set of rules that are followed by calculations and processes by computers. Learning how to design and analyze algorithms will put you in an advantage for your professional growth and development. This Algorithms Design and Analysis Diploma will introduce you the teaching techniques focusing on the design and analysis of ef cient algorithm with emphasis on the methods of application. You will be provided with information on dynamic programming, complexity, etc. here.
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 Edukite courses are free to study. To successfully complete a course you must submit all the assignment of the course as part of the assessment. Upon successful completion of a course, you can choose to make your achievement formal by obtaining your Certi cate at a cost of £49. Having an Of cial Edukite Certi cation is a great way to celebrate and share your success. You can: Add the certi cate to your CV or resume and brighten up your career Show it to prove your success https://edukite.org/course/algorithms-design-and-analysis-diploma/
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Course Credit: MIT
COURSE CURRICULUM
TWO MOTIVATING APPLICATIONS
Application: Internet Routing
00:11:00
Application: Sequence Alignment
00:09:00
INTRODUCTION TO GREEDY ALGORITHMS
Introduction to Greedy Algorithms
00:13:00
Application: Optimal Caching
00:11:00
A SCHEDULING APPLICATION
Problem De nition
00:06:00
A Greedy Algorithm
00:13:00
Correctness Proof – Part I
00:07:00
Correctness Proof – Part II
00:05:00
Handling Ties [Advanced – Optional]
00:07:00
PRIM'S MINIMUM SPANNING TREE ALGORITHM
MST Problem De nition
00:11:00
Prim’s MST Algorithm
00:07:00
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Algorithms Design and Analysis Diploma - Edukite
Correctness Proof
00:16:00
Correctness Proof II
00:08:00
Proof of Cut Property [Advanced – Optional]
00:12:00
Fast Implementation I
00:15:00
Fast Implementation II
00:10:00
KRUSKAL'S MINIMUM SPANNING TREE ALGORITHM
Kruskal’s MST Algorithm
00:08:00
Correctness of Kruskal’s Algorithm
00:10:00
Implementing Kruskal’s Algorithm via Union-Find
00:10:00
Implementing Kruskal’s Algorithm via Union-Find II
00:14:00
MSTs: State-of-the-Art and Open Questions [Advanced – Optional]
00:09:00
CLUSTERING
Application to Clustering
00:11:00
Correctness of Clustering Algorithm
00:10:00
ADVANCED UNION-FIND
Lazy Unions [Advanced – Optional]
00:10:00
Union-by-Rank [Advanced – Optional]
00:12:00
Analysis of Union-by-Rank [Advanced – Optional]
00:15:00
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Algorithms Design and Analysis Diploma - Edukite
Path Compression [Advanced – Optional]
00:15:00
Path Compression: The Hopcroft-Ullman Analysis I [Advanced – Optional]
00:10:00
Path Compression: The Hopcroft-Ullman Analysis II [Advanced – Optional]
00:12:00
The Ackermann Function [Advanced – Optional]
00:16:00
Path Compression: Tarjan’s Analysis I [Advanced – Optional]
00:14:00
Path Compression: Tarjan’s Analysis II [Advanced – Optional]
00:14:00
HUFFMAN CODES
Introduction and Motivation
00:09:00
Problem De nition
00:10:00
A Greedy Algorithm
00:17:00
A More Complex Example
00:04:00
Correctness Proof I
00:10:00
Correctness Proof II
00:13:00
INTRODUCTION TO DYNAMIC PROGRAMMING
Introduction: Weighted Independent Sets in Path Graphs
00:08:00
WIS in Path Graphs: A Linear-Time Algorithm
00:10:00
WIS in Path Graphs: A Reconstruction Algorithm
00:07:00
Principles of Dynamic Programming
00:08:00
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Algorithms Design and Analysis Diploma - Edukite
THE KNAPSACK PROBLEM
The Knapsack Problem
00:10:00
A Dynamic Programming Algorithm
00:10:00
Example [Review – Optional]
00:13:00
SEQUENCE ALIGNMENT
Optimal Substructure
00:14:00
A Dynamic Programming Algorithm
00:12:00
OPTIMAL BINARY SEARCH TREES
Problem De nition
00:13:00
Optimal Substructure
00:10:00
Proof of Optimal Substructure
00:07:00
A Dynamic Programming Algorithm
00:10:00
A Dynamic Programming Algorithm II
00:10:00
THE BELLMAN-FORD ALGORITHM
Single-Source Shortest Paths, Revisited
00:11:00
Optimal Substructure
00:11:00
The Basic Algorithm I
00:09:00
The Basic Algorithm II
00:11:00
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Algorithms Design and Analysis Diploma - Edukite
Detecting Negative Cycles
00:09:00
A Space Optimization
00:13:00
Internet Routing I [Optional]
00:12:00
Internet Routing II
00:07:00
ALL-PAIRS SHORTEST PATHS
Problem De nition
00:07:00
Optimal Substructure
00:12:00
The Floyd-Warshall Algorithm
00:14:00
A Reweighting Technique
00:14:00
Johnson’s Algorithm
00:11:00
Johnson’s Algorithm II
00:12:00
NP-COMPLETE PROBLEMS
Polynomial-Time Solvable Problems
00:15:00
Reductions and Completeness
00:14:00
De nition and Interpretation of NP-Completeness I
00:11:00
De nition and Interpretation of NP-Completeness II
00:08:00
The P vs. NP Question
00:09:00
Algorithmic Approaches to NP-Complete Problems
00:13:00
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Algorithms Design and Analysis Diploma - Edukite
FASTER EXACT ALGORITHMS FOR NP-COMPLETE PROBLEMS
The Vertex Cover Problem
00:09:00
Smarter Search for Vertex I
00:10:00
Smarter Search for Vertex Cover II
00:08:00
The Traveling Salesman Problem
00:15:00
A Dynamic Programming Algorithm for TSP
00:12:00
APPROXIMATION ALGORITHMS FOR NP-COMPLETE PROBLEMS
A Greedy Knapsack Heuristic
00:14:00
Analysis of a Greedy Knapsack Heuristic I
00:07:00
Analysis of a Greedy Knapsack Heuristic II
00:10:00
A Dynamic Programming Heuristic for Knapsack
00:12:00
Knapsack via Dynamic Programming, Revisited
00:11:00
Analysis of Dynamic Programming Heuristic
00:15:00
LOCAL SEARCH ALGORITHMS
The Maximum Cut Problem I
00:09:00
The Maximum Cut Problem II
00:09:00
Principles of Local Search I
00:09:00
Principles of Local Search II
00:11:00
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The 2-SAT Problem
00:15:00
Random Walks on a Line
00:16:00
Analysis of Papadimitriou’s Algorithm
00:15:00
THE WIDER WORLD OF ALGORITHMS
Stable Matching [Optional]
00:15:00
Matchings, Flows, and Braess’s Paradox [Optional]
00:14:00
Linear Programming and Beyond [Optional]
00:12:00
Epilogue
00:01:00
Assessment
Submit Your Assignment
00:00:00
Certi cation
00:00:00
COURSE REVIEWS
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