Course Name: Randomized Algorithms

Course abstract

Algorithms are required to be correct" and fast". In a wide variety of ap- plications, these twin objectives are in conflict with each other. Fortunately, neither of these ideals are sacrosanct. Therefore we can often try to optimize one of these goals by incurring a small penalty on the other. This takes us to the field of Randomized Algorithms. Often, the randomized variants, in addition to being faster than their deterministic counterpart, are simpler to understand and implement. In this course, we will study this trade off between correctness and speed. We will be learning a number of methods to design and analyze randomized algorithms.


Course Instructor

Media Object

Prof. Benny George K

Dr Benny George K is an Assistant Professor in the Department of Computer Science and Engineering at IIT Guwahati. He is interested in theoretical aspects of computer science.
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Teaching Assistant(s)

Badri Prasad Nanda

PhD

MRITYUNJAY SINGH

PhD Computer Science

 Course Duration : Jan-Apr 2019

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 Syllabus

 Enrollment : 15-Nov-2018 to 28-Jan-2019

 Exam registration : 28-Jan-2019 to 19-Apr-2019

 Exam Date : 27-Apr-2019, 27-Apr-2019

Enrolled

2111

Registered

220

Certificate Eligible

82

Certified Category Count

Gold

1

Silver

7

Elite

16

Successfully completed

58

Participation

98

Success

Elite

Silver

Gold





Legend

>=90 - Elite + Gold
75-89 -Elite + Silver
>=60 - Elite
40-59 - Successfully Completed
<40 - No Certificate

Final Score Calculation Logic

  • Assignment Score = Average of best 8 out of 12 assignments.
  • Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score
Randomized Algorithms - Toppers list

CHHARCHHODAWALA MOHAMMAD HUSENIBHAI 93%

ONLINEPSBLOANS

BIKASH MAZUMDAR 88%

TEZPUR UNIVERSITY

SHAKEEL AHMAD DAR 87%

DEPTT OF TECHNICAL EDUCATION ,J&K GOVT

DISHA PATEL 86%

COLLEGE OF ENGINEERING PUNE

MANISH KUMAR 86%

INDIAN STATISTICAL INSTITUTE KOLKATA

Enrollment Statistics

Total Enrollment: 2111

Registration Statistics

Total Registration : 220

Assignment Statistics




Assignment

Exam score

Final score

Score Distribution Graph - Legend

Assignment Score: Distribution of average scores garnered by students per assignment.
Exam Score : Distribution of the final exam score of students.
Final Score : Distribution of the combined score of assignments and final exam, based on the score logic.