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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 [course_title] will introduce you the teaching techniques focusing on the design and analysis of efficient 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 Certificate at a cost of £49.

Having an Official Edukite Certification is a great way to celebrate and share your success. You can:

• Show it to prove your success

Course Credit: MIT

### Course Curriculum

 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 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

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