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Algorithms Design and Analysis Diploma - Edukite

HOME / COURSE / PERSONAL DEVELOPMENT / ALGORITHMS DESIGN AND ANALYSIS DIPLOMA

Algorithms Design and Analysis Diploma ( 9 REVIEWS ) 

477 STUDENTS

The algorithm is the set of rules that are followed by calculations and processes by computers. Learning how to design …

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FREE

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1 YEAR LEVEL 3 - DIPLOMA COURSE BADGE COURSE CERTIFICATE

96

NUMBER OF UNITS NUMBER OF QUIZZES

0

17 HOURS, 8 MINUTES

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CURRICULUM

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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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Algorithms Design and Analysis Diploma - Edukite

  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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Algorithms Design and Analysis Diploma - Edukite

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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Algorithms Design and Analysis - Edukite  

Welcome to the self-paced course, Algorithms: Design and Analysis! Algorithms are the heart of computer science, and the subject has countle...

Algorithms Design and Analysis - Edukite  

Welcome to the self-paced course, Algorithms: Design and Analysis! Algorithms are the heart of computer science, and the subject has countle...

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