Course Name: Introduction to Data Analytics

Course abstract

Data Analytics is the science of analyzing data to convert information to useful knowledge. This knowledge could help us understand our world better, and in many contexts enable us to make better decisions. While this is the broad and grand objective, the last 20 years has seen steeply decreasing costs to gather, store, and process data, creating an even stronger motivation for the use of empirical approaches to problem solving. This course seeks to present you with a wide range of data analytic techniques and is structured around the broad contours of the different types of data analytics, namely, descriptive, inferential, predictive, and prescriptive analytics.


Course Instructor

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Prof. Nandan Sudarsanam

Dr. Nandan Sudarsanam holds a Ph.D. in Engineering Systems from Massachusetts Institute of Technology (MIT). His research interests and work experience spans the areas of Data mining/ Machine learning, Experimentation, Applied Statistics, and Algorithmic approaches to problem solving. Dr. Nandan currently works as a faculty member at the Department of Management Studies at IIT-Madras.


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Prof. Balaraman Ravindran

Dr. Balaraman Ravindran completed his Ph.D. at the Department of Computer Science, University of Massachusetts, Amherst. He worked with Prof. Andrew G. Barto on an algebraic framework for abstraction in Reinforcement Learning. Dr. Ravindran’s current research interests spans the broader area of machine learning, ranging from Spatiotemporal Abstractions in Reinforcement Learning to social network analysis and Data/Text Mining.


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Teaching Assistant(s)

Tarun Kumar

Research Scholar, IITM

 Course Duration : Jul-Sep 2017
  View Course
 Enrollment : 17-May-2017 to 24-Jul-2017
 Exam registration : 02-Aug-2017 to 23-Aug-2017
 Exam Date : 24-Sep-2017

Enrolled

8654

Registered

652

Certificate Eligible

461

Certified Category Count

Gold

2

Silver

0

Elite

208

Successfully completed

251

Participation

61

Success

Elite

Gold




Legend

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

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 Data Analytics - Toppers list
Top 1 % of Certified Candidates

SHAILESH KUMAR JHA 92%

TTSL

E SANTHOSH KUMAR 90%

INDIAN INSTITUTE OF TECHNOLOGY MADRAS

MILAN ROY 88%

IIT DELHI

RAMARCHA KUMAR 88%

GALGOTIAS UNIVERSITY

DIPJYOTI BISHARAD 88%

NATIONAL INSTITUTE OF TECHNOLOGY SILCHAR


Top 2 % of Certified Candidates

LOKESH KUMAR T 85%

INDIAN INSTITUTE OF TECHNOLOGY MADRAS

SAURABH KUMAR 84%

ORACLE INDIA PRIVATE LIMITED

PRERANA CHAUHAN 83%

UNEMPLOYED

SUSHANT DOGRA 83%

INDIAN INSTITUTE OF TECHNOLOGY MADRAS

PANKAJ VERMA 83%

ACCOUNTANT GENERAL


Top 5 % of Certified Candidates

SIDDHARTH BHATIA 82%

INDIAN INSTITUTE OF TECHNOLOGY MADRAS

SUMAN KALYAN GHOSH 82%

ALLIANCE UNIVERSITY

PRAVIN MHASKE 81%

INFOSYS

ADARSH RAMACHANDRA RAO 81%

INFOSYS LTD

DIPANWITA GANGOPADHYAY 81%

NA

HRIDAY ANAND NISSANKARA 80%

NONE

APARNAA RAMANATHAN 80%

LATENTVIEW ANALYTICS PVT LTD

HAMSA S 80%

RV COLLEGE OF ENGINEERING

KRISHNAMOHAN M 79%

PAG OFFICE TRIVANDRUM

NILESH SITARAM GARDI 79%

MUMBAI UNIVERSITY

ROHITH SRINIVAAS M 79%

INDIAN INSTITUTE OF TECHNOLOGY MADRAS

NITIN RADKE 79%

SHRI SHANKARACHARYA TECHNICAL CAMPUS

ANUP ABDUL KHALAM 78%

FREELANCE

Enrollment Statistics

Total Enrollment: 8654

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Data Not Found..!

Assignment Statistics



Feedback Videos

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.