Course Name: Algorithms for Big Data

Course abstract

Traditional algorithms works well when the input data fits entirely within memory. In many modern application contexts, however, the size of the input data is too large to fit within memory. In some cases, data is stored in large data centres or clouds and specific parts of it can be accessed via queries. In some other application contexts, very large volume of data may stream through a computer one item at a time. So the algorithm will get to see the data typically as a single pass, but will not be able to store the data for future reference. In this course, we will introduce computational models, algorithms and analysis techniques aimed at addressing such big data contexts.


Course Instructor

Media Object

Prof. John Augustine

Dr. John Augustine is an Assistant Professor in the Department of Computer Science and Engineering at IIT Madras. He received his Ph.D. in Computer Science from the University of California at Irvine in 2006. Prior to IIT Madras, he worked as a scientist at Tata Research Development and Design Centre in Pune and also as a Research Fellow at Nanyang Technological University. He has a wide array of research interests ranging from distributed network algorithms (esp., dynamic network algorithms), online algorithms, computational geometry, combinatorial optimization, and also applied algorithms, esp., in the context of inexact computing.
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Teaching Assistant(s)

JITHIN VACHERY

ME - CompSc & Engg
PhD-CompSc & Engg

WILLIAM KUMAR MOSES Jr.

 Course Duration : Jul-Sep 2016

  View Course

 Syllabus

 Enrollment : 23-May-2016 to 18-Jul-2016

 Exam registration : 02-Aug-2016 to 19-Aug-2016

 Exam Date : 18-Sep-2016, 25-Sep-2016

Enrolled

6011

Registered

95

Certificate Eligible

68

Certified Category Count

Gold

0

Elite

45

Successfully completed

23

Participation

0

Success

Elite

Gold





Legend

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

Final Score Calculation Logic

  • Assignment Score = Average of best 6 out of 8 assignments
  • Exam Score = 100%
  • Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score
  • Final certificate score have been moderated by faculty
Algorithms for Big Data - Toppers list

JAI LUTHRA 86%

INDRAPRASTHA INSTITUTE OF INFORMATION TECHNOLOGY

MOHANDAS SREENIVASAN 86%

HONEYWELL

ASHISH KUMAR 85%

TECHNO INDIA, SALT LAKE, WEST BENGAL

SANTOSH KUMAR RAVVA 85%

MAHARAJ VIJAYARAM GAJAPATHI RAJ COLLEGE OF ENGINEERING

ANUSHA P 85%

SVIT

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.