Course Name: Social Networks

Course abstract

The network of friendships on Facebook, road connections, terrorist networks and disease spreading networks are today available as a graph G(V,E). Social Network Analysis involves discerning this graph data and making sense out of it. The course will revolve around the study of some well-known theories of social and information networks and their applications on real world datasets.


Course Instructor

Media Object

Prof. Sudarshan Iyengar

Sudarshan Iyengar has a Ph.D. from the Indian Institute of Science and is currently working as an assistant professor at IIT Ropar and has been teaching this course from the past 5 years. Apart from this course, he has offered several other courses in IIT Ropar like Discrete Mathematics, Theory of Computation, Cryptography, Probability and Computing etc. His research interests include social networks, crowdscoured knowledge building and computational social sciences. His current research proects are "Predicting a Viral meme" (Yayati Gupta), "Understanding Crowdsourced Knowledge buidling" (Anamika Chhabra - Scientist), "Secure Computation" (Varsha Bhat) and "Network Sampling" (Akrati Saxena). After research, teaching makes the major component of his academic life. He enjoys experimenting with different teaching methodologies. He particularly enjoys traveling and giving talks on his research work apart from motivational talks of popsci genre.


Teaching Assistant(s)

Gokul Karthik

B.Tech. Information Technology

Anamika Chhabra

Ph.D., Computer Science

Yayati Gupta

Ph.D., Computer Science

 Course Duration : Jan-Apr 2018
  View Course
 Syllabus
 Enrollment : 20-Nov-2017 to 22-Jan-2018
 Exam registration : 08-Jan-2018 to 07-Mar-2018
 Exam Date : 28-Apr-2018, 29-Apr-2018

Enrolled

5188

Registered

214

Certificate Eligible

148

Certified Category Count

Gold

8

Elite

86

Successfully completed

54

Participation

52

Success

Elite

Gold




Legend

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

Final Score Calculation Logic

  • Assignment Score = 15% of 8 out of 12 quiz+10% of 4 out of 6 Programming assignment.
  • Exam Score = 75% of Certification Exam Score out of 100 FINAL SCORE (Score on Certificate) = Exam Score + Assignment Score
  • NOTE:A13,A14,A15,A16,A17,A18 are programming Assignments We have taken the average of all programming assignment in a particular week
Social Networks - Toppers list
Top 1 % of Certified Candidates

M. VIJAYALAKSHMI 94%

VIVEKANAND EDUCATION SOCIETY INSTITUTE OF TECHNOLOGY

DIPAN CHAKRABORTY 94%

ST.THOMAS COLLEGE OF ENGINEERING & TECHNOLOGY


Top 2 % of Certified Candidates

MITHAGARI AMEYA MILIND 93%

BHARATIYA VIDYA BHAVANS SARDAR PATEL INSTITUTE OF TECHNOLOGY


Top 5 % of Certified Candidates

SHAH PARTH RAJNIKANT 92%

BIRLA VISHVAKARMA MAHAVIDYALAYA ENGINEERING COLLEGE

GAURAV MISRA 92%

INDIAN INSTITUTE OF INFORMATION TECHNOLOGY KALYANI

RAVICHANDRAN N 92%

PSG COLLEGE OF TECHNOLOGY

AKANKSHA ACHANTI 90%

CMR INSTITUTE OF TECHNOLOGY

SHYAM SUNDAR MEENA 90%

SWAMI VIVEKANAND COLLEGE OF ENGINEERING, INDORE

Enrollment Statistics

Total Enrollment: 5188

Registration Statistics

Total Registration : 214

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.