Course Name: Introduction to Soft Computing

Course abstract

Soft computing is an emerging approach to computing which parallel the remarkable ability of the human mind to reason and learn in an environment of uncertainty and imprecision. Soft computing is based on some biological inspired methodologies such as genetics, evolution, ant’s behaviors, particles swarming, human nervous systems, etc. Now, soft computing is the only solution when we don’t have any mathematical modeling of problem solving (i.e., algorithm), need a solution to a complex problem in real time, easy to adapt with changed scenario and can be implemented with parallel computing. It has enormous applications in many application areas such as medical diagnosis, computer vision, hand written character recondition, pattern recognition, machine intelligence, weather forecasting, network optimization, VLSI design, etc.


Course Instructor

Media Object

Prof. Debasis Samanta

Debasis Samanta holds a Ph.D. in Computer Science and Engineering from Indian Institute of Technology Kharagpur. His research interests and work experience spans the areas of Computational Intelligence, Data Analytics, Human Computer Interaction, Brain Computing and Biometric Systems. Dr. Samanta currently works as a faculty member at the Department of Computer Science & Engineering at IIT Kharagpur.


Teaching Assistant(s)

Arpita Chaudhuri

P.hD

 Course Duration : Jan-Mar 2020

  View Course

 Enrollment : 18-Nov-2019 to 03-Feb-2020

 Exam registration : 16-Dec-2019 to 21-Feb-2020

 Exam Date : 29-Mar-2020

Enrolled

3173

Registered

71

Certificate Eligible

53

Certified Category Count

Gold

1

Silver

22

Elite

19

Successfully completed

11

Participation

7

Success

Elite

Silver

Gold





Legend

AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75 AND FINAL SCORE >=40
BASED ON THE FINAL SCORE, Certificate criteria will be as below:
>=90 - Elite + Gold
75-89 -Elite + Silver
>=60 - Elite
40-59 - Successfully Completed

Final Score Calculation Logic

  • Assignment Score = Average of best 6 out of 8 assignments.
  • Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score
Introduction to Soft Computing - Toppers list

HARSHA SUDHEER 90%

MUTHOOT INSTITUTE OF TECHNOLOGY & SCIENCE

JAY KANT PRATAP SINGH YADAV 88%

AJAY KUMAR GARG ENGINEERING COLLEGE

ARINDAM CHAKRAVORTY 86%

ST.THOMAS COLLEGE OF ENGINEERING AND TECHNOLOGY

SREERAG S 84%

AMMINI COLLEGE OF ENGINEERING

DHIVYA S 84%

VIT UNIVERSITY CHENNAI

S.V.ADITHIYA 84%

VIT UNIVERSITY-VELLORE

Enrollment Statistics

Total Enrollment: 3173

Registration Statistics

Total Registration : 468

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.