Course Name: Natural Language Processing

Course abstract

This course starts with the basics of text processing including basic pre-processing, spelling correction, language modeling, Part-of-Speech tagging, Constituency and Dependency Parsing, Lexical Semantics, distributional Semantics and topic models. Finally, the course also covers some of the interesting applications of text mining such as entity linking, relation extraction, text summarization, text classification, sentiment analysis and opinion mining.


Course Instructor

Media Object

Prof. Pawan Goyal

Pawan Goyal joined the Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur as an Assistant Professor on July 30th, 2013. Prior to that, he was working at INRIA Paris-Rocquencourt as a post doctoral fellow with Prof. Gérard Huet on The Sanskrit Heritage Site. He did his B. Tech. in Electrical Engineering from Indian Institute of Technology, Kanpur. He received his Ph. D. from Intelligent Systems Research Centre, Faculty of Computing and Engineering, University of Ulster, UK. His main research interests include Text Mining, Natural Language Processing, Information Retrieval and Sanskrit Computational Linguistics. He has published over 40 research articles in various CS journals and conferences including ACL, Coling, TKDE, CACM, KDD, CIKM, JCDL.
More info

Teaching Assistant(s)

Bishal Santra

P.hD

Kalyani Roy

P.hD

Rajdeep Mukherjee

P.hD

 Course Duration : Jul-Oct 2019
  View Course
 Enrollment : 15-May-2019 to 05-Aug-2019
 Exam registration : 01-Jun-2019 to 30-Sep-2019
 Exam Date : 16-Nov-2019

Enrolled

4161

Registered

252

Certificate Eligible

123

Certified Category Count

Gold

0

Silver

9

Elite

43

Successfully completed

71

Participation

72

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.
Natural Language Processing - Toppers list
Top 1 % of Certified Candidates

SHIRSHENDRANATH PAUL 82%

G H RAISONI INSTITUTE OF ENGINEERING AND TECHNOLOGY,NAGPUR


Top 2 % of Certified Candidates

PANDYA HARIOM ASHOKKUMAR 81%

DHARMSINH DESAI UNIVERSITY,NADIAD


Top 5 % of Certified Candidates

NIKITA PARITOSH DESAI 78%

DHARMSINH DESAI UNIVERSITY,NADIAD

ANIRUDH KAMATH 78%

BHARATIYA VIDYA BHAVANS SARDAR PATEL INSTITUTE OF TECHNOLOGY

SIDDHARTH SHAH 78%

DHARMSINH DESAI UNIVERSITY,NADIAD

YASHODHARA HARIBHAKTA 77%

COLLEGE OF ENGINEERING PUNE

ADITYA KUMAWAT 77%

INDIAN INSTITUTE OF TECHNOLOGY,ROORKEE

Enrollment Statistics

Total Enrollment: -1

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Registration Statistics

Total Registration : 252

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.