Course Name: Deep Learning

Course abstract

The availability of huge volume of Image and Video data over the internet has made the problem of data analysis and interpretation a really challenging task. Deep Learning has proved itself to be a possible solution to such Computer Vision tasks. Not only in Computer Vision, Deep Learning techniques are also widely applied in Natural Language Processing tasks. In this course we will start with traditional Machine Learning approaches, e.g. Bayesian Classification, Multilayer Perceptron etc. and then move to modern Deep Learning architectures like Convolutional Neural Networks, Autoencoders etc. On completion of the course students will acquire the knowledge of applying Deep Learning techniques to solve various real life problems.


Course Instructor

Media Object

Prof. Prabir Kumar Biswas

Dr. Prabir Kr. Biswas completed his B.Tech(Hons), M.Tech and Ph.D from the Department of Electronics and Electrical Communication Engineering, IIT Kharagpur, India in the year 1985, 1989 and 1991 respectively. From 1985 to 1987 he was with Bharat Electronics Ltd. Ghaziabad as a deputy engineer. Since 1991 he has been working as a faculty member in the department of Electronics and Electrical Communication Engineering, IIT Kharagpur, where he is currently holding the position of Professor and Head of the Department. Prof. Biswas visited University of Kaiserslautern, Germany under the Alexander von Humboldt Research Fellowship during March 2002 to February 2003. Prof. Biswas has more than a hundred research publications in international and national journals and conferences and has filed seven international patents. His area of interest are image processing, pattern recognition, computer vision, video compression, parallel and distributed processing and computer networks. He is a senior member of IEEE and was the chairman of the IEEE Kharagpur Section, 2008.
More info

Teaching Assistant(s)

Aupendu Kar

P.hD

Manashi Chakraborty

P.hD

 Course Duration : Jan-Apr 2020
  View Course
 Enrollment : 18-Nov-2019 to 03-Feb-2020
 Exam registration : 16-Dec-2019 to 20-Mar-2020
 Exam Date : 25-Apr-2020

Enrolled

11645

Registered

261

Certificate Eligible

179

Certified Category Count

Gold

3

Silver

49

Elite

82

Successfully completed

45

Participation

21

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 8 out of 12 assignments.
  • Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score
Deep Learning - Toppers list
Top 1 % of Certified Candidates

SUMANTH V G 95%

MAHATMA GANDHI INSTITUTE OF TECHNOLOGY

VISHAKHA SUBODH KORDE 93%

COLLEGE OF ENGINEERING PUNE


Top 2 % of Certified Candidates

MANJUNATH S 92%

Rakuten India

KUNDAM VENKATA NIKHIL 88%

CMR TECHNICAL CAMPUS


Top 5 % of Certified Candidates

M. SABRIGIRIRAJ 87%

SVS COLLEGE OF ENGINEERING

VINEETH REDDY MOTATI 87%

AURORA`S TECHNOLOGICAL AND RESEARCH INSTITUTE

DHANUSHREE M 86%

Anna university, CEG Campus, chennai

DHIRAJ MUKESH JHA 85%

GOVT.COLLEGE OF ENGINEERING

PRAFFUL KUMAR KHOBA 85%

Indian Institute of Technology,Roorkee

Enrollment Statistics

Total Enrollment: 11645

Registration Statistics

Total Registration : 1303

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.