Course Name: Data Analytics with Python

Course abstract

We are looking forward to sharing many exciting stories and examples of analytics with all of you using python programming language. This course includes examples of analytics in a wide variety of industries, and we hope that students will learn how you can use analytics in their career and life. One of the most important aspects of this course is that you, the student, are getting hands-on experience creating analytics models; we, the course team, urge you to participate in the discussion forums and to use all the tools available to you while you are in the course!


Course Instructor

Media Object

Prof. A Ramesh

Ramesh Anbanandam graduated in Production Engineering from Madras University, Chennai. He did his post-graduation from National Institute of Technology, Trichy. He later earned his Ph.D. in Supply Chain Management from Indian Institute of Technology Delhi. His professional interest includes Humanitarian Supply Chain Management, Operations Management, Operations Research, Healthcare Waste Management, Sustainable Multi-model and Freight Transportation, Transportation Asset Management and Advanced Data Analytics using Python and R- programming. He has guided Ph.D. thesis in the area of Humanitarian Supply Chain Management, Healthcare waste management, and Reverse Logistics. He has published various research articles in reputed journals. He was also awarded Emerald Literati Award for Excellence under “Highly Commended Research Paper in the Year 2011 and 2016” in the field of Supply Chain Management.
More info

Teaching Assistant(s)

Shaurya Mall

P.hD

Umabharati Rawat

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

29374

Registered

423

Certificate Eligible

273

Certified Category Count

Gold

2

Silver

62

Elite

103

Successfully completed

106

Participation

62

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
Data Analytics with Python - Toppers list
Top 1 % of Certified Candidates

DIVYANSH GUPTA 90%

NATIONAL INSTITUTE OF TECHNOLOGY PATNA

MUSKAN KUMARI 90%

NATIONAL INSTITUTE OF TECHNOLOGY PATNA

APURVA PARASHAR 87%

NATIONAL INSTITUTE OF TECHNOLOGY PATNA


Top 2 % of Certified Candidates

PRIYANSHU KUMAR 86%

NATIONAL INSTITUTE OF TECHNOLOGY PATNA

SUNIL KISHORKUMAR VITHALANI 86%

DHARMSINH DESAI UNIVERSITY,NADIAD

AMAN AMBASHTA 86%

NATIONAL INSTITUTE OF TECHNOLOGY PATNA


Top 5 % of Certified Candidates

SUJEETH SARAVAN RAJ S 85%

Comcast

ADITYA DASH 84%

COLLEGE OF ENGINEERING AND TECHNOLOGY, BHUBANESWAR

NIKHIL KUMAR 84%

NATIONAL INSTITUTE OF TECHNOLOGY PATNA

MUTHUKRISHNAN.R 84%

BHARATHIAR UNIVERSITY, COIMBATORE, TAMILNADU

MOHNISH SATIDASANI 84%

NATIONAL INSTITUTE OF TECHNOLOGY PATNA

ANIKET KUMAR 84%

NATIONAL INSTITUTE OF TECHNOLOGY PATNA

RAJKUMAR LAKSHMANAMOORTHY 83%

NIRO PROJECTS

RISHABH SHARMA 83%

NATIONAL INSTITUTE OF TECHNOLOGY PATNA

SATHIYA NARAYANAN S 83%

VIT UNIVERSITY CHENNAI

GAURAV 83%

NATIONAL INSTITUTE OF TECHNOLOGY PATNA

DEETI HOTHRIK 83%

NATIONAL INSTITUTE OF TECHNOLOGY PATNA

Enrollment Statistics

Total Enrollment: 29374

Registration Statistics

Total Registration : 3330

Assignment Statistics



This course perfectly planned and executed as per the schedule All  video lectures are informative and very useful for my research also.


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.