Objective of this course is to impart knowledge on use of data mining techniques for deriving business intelligence to achieve organizational goals. Use of R (statistical computingCSS - MOOCs Proposal software) to build, assess, and compare models based on real datasets and cases with an easy-to-follow learning curve.
INTENTED AUDIENCE :Nil
CORE/ELECTIVE : Elective
UG or PG COURSE :Both
PRE REQUISITES : Basic Statistics Knowledge
SUPPORTED INDUSTRIES :Big Data companies, Analytics & Consultancy companies, Companies with Analytics Division
3455 students have enrolled already!!
Dr. Gaurav Dixitis an Assistant Professor in the Department of Management Studies at the Indian Institute of Technology Roorkee. He earned his doctoral degree from the Indian Institute of Management Indore and an engineering degree from Indian Institute of Technology (BHU) Varanasi. Previously, he worked in Hewlett-Packard (HP) as software engineer, and Sharda Group of Institutions as project manager on deputation.
Gaurav’s research focuses on information technology (IT) strategy for business, society, and governance, electronic commerce, enterprise software, data mining & big data analytics and provides insights on business value of information technology. His research has appeared in quality journals & conferences, including Journal of Global Information Technology Management, Journal of Information Technology Management, India Finance Conference, Indian Academy of Management, and Academy of Management.
Overview of Data Mining and its Components Introduction and Data Mining
Process Introduction to R Basic Statistical Techniques Week2:Data Preparation and Exploration Visualization Techniques Week3:Data Preparation and Exploration Visualization Techniques Dimension Reduction Techniques Principal Component Analysis Week4:Performance Metrics and Assessment Performance Metrics for Prediction and Classification Week5:Supervised Learning Methods Multiple Linear Regression Week6:Supervised Learning Methods Multiple Linear Regression Week7:Supervised Learning Methods NaÃ ̄ve Bayes Week8:Supervised Learning Methods Classification & Regression Trees Week9:Supervised Learning Methods Classification & Regression Trees Week10:Supervised Learning Methods Logistic Regression Week11:Supervised Learning Methods Logistic Regression Artificial Neural Networks Week12:Supervised Learning Methods and Wrap Up Artificial Neural Networks Discriminant Analysis Conclusion
Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data by EMC Education Services (2015)
Mining for Business Intelligence: Concepts,Techniques, and Applications
in Microsoft Office Excel with XLMiner by Shmueli, G., Patel, N. R.,
& Bruce, P. C. (2010)
The exam is optional for a fee.
Date and Time of Exams: April 28 (Saturday) and April 29 (Sunday) : Afternoon session: 2pm to 5pm
Exam for this course will be available in one session on both 28 and 29 April.
Registration url: Announcements will be made when the registration form is open for registrations.
The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published.
Final score will be calculated as : 25% assignment score + 75% final exam score
25% assignment score is calculated as 25% of average of Best 8 out of 12 assignments
E-Certificate will be given to those who register and write the exam and score greater than or equal to 40% final score. Certificate will have your name, photograph and the score in the final exam with the breakup. It will have the logos of NPTEL and IIT ROORKEE. It will be e-verifiable at nptel.ac.in/noc