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. See More: https://bit.ly/2V1Jl3N

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Algorithms Design and Analysis
Diploma
( 8 REVIEWS ) 372 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
1 YEAR
LEVEL 3 - DIPLOMA
COURSE BADGE
COURSE CERTIFICATE
25NUMBER OF UNITS
0NUMBER OF QUIZZES
18 HOURS, 19 MINUTES
HOME CURRICULUM REVIEWS
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:
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Course Credit: MIT
Lecture 1: Overview, Interval Scheduling 00:24:00
Lecture 2: Divide & Conquer: Convex Hull, Median Finding 00:21:00
Lecture 3: Divide & Conquer: FFT 00:21:00
Lecture 4: Divide & Conquer: van Emde Boas Trees 00:20:00
Lecture 5: Amortization: Amortized Analysis 00:16:00
Lecture 6: Randomization: Matrix Multiply, Quicksort 00:22:00
Lecture 7: Randomization: Skip Lists 00:21:00
Lecture 8: Randomization: Universal & Perfect Hashing 00:22:00
Lecture 9: Augmentation: Range Trees 00:25:00
Lecture 10: Dynamic Programming: Advanced DP 00:20:00
Lecture 11: Dynamic Programming: All-Pairs Shortest Paths 00:22:00
Lecture 12: Greedy Algorithms: Minimum Spanning Tree 00:22:00
Lecture 13: Incremental Improvement: Max Flow, Min Cut 00:23:00
Lecture 14: Incremental Improvement: Matching 00:23:00
Lecture 15: Linear Programming: LP, reductions, Simplex 01:22:00
Lecture 16: Complexity: P, NP, NP-completeness, Reductions 01:25:00
COURSE CURRICULUM

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Lecture 17: Complexity: Approximation Algorithms 01:21:00
Lecture 18: Complexity: Fixed-Parameter Algorithms 01:17:00
Lecture 19: Synchronous Distributed Algorithms: Symmetry-Breaking.
Shortest-Paths Spanning Trees
01:17:00
Lecture 20: Asynchronous Distributed Algorithms: Shortest-Paths
Spanning Tree
01:12:00
Lecture 21: Cryptography: Hash Functions 01:22:00
Lecture 22: Cryptography: Encryption 01:24:00
Lecture 23: Cache-Oblivious Algorithms: Medians & Matrices 01:20:00
Lecture 24: Cache-Oblivious Algorithms: Searching & Sorting 01:17:00
Assessment
Submit Your Assignment 00:00:00
COURSE REVIEWS
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