Business Analytics & Data Mining Modeling Using R Course | IIT Roorkee
Course Details
| Exam Registration | 646 |
|---|---|
| Course Status | Ongoing |
| Course Type | Elective |
| Language | English |
| Duration | 12 weeks |
| Categories | Management Studies |
| Credit Points | 3 |
| Level | Undergraduate/Postgraduate |
| Start Date | 19 Jan 2026 |
| End Date | 10 Apr 2026 |
| Enrollment Ends | 02 Feb 2026 |
| Exam Registration Ends | 20 Feb 2026 |
| Exam Date | 18 Apr 2026 IST |
| NCrF Level | 4.5 — 8.0 |
Unlock the Power of Data: A 12-Week Journey into Business Analytics & Data Mining with R
In today's data-driven world, the ability to extract meaningful insights from vast amounts of information is a critical skill for any business professional. The course "Business Analytics and Data Mining Modeling using R", offered by the prestigious Indian Institute of Technology Roorkee, is designed to equip you with precisely these skills. Over 12 intensive weeks, this program provides a robust foundation in using the powerful R statistical software to solve real-world business problems.
Meet Your Expert Instructor: Prof. Gaurav Dixit
Leading this course is Prof. Gaurav Dixit, an Assistant Professor in the Department of Management Studies at IIT Roorkee. Prof. Dixit brings a rare blend of high-caliber academic expertise and valuable industry experience to the classroom.
- Academic Credentials: He holds a doctoral degree from IIM Indore and an engineering degree from IIT (BHU) Varanasi.
- Industry Experience: His professional background includes roles as a Software Engineer at Hewlett-Packard (HP) and as a Project Manager.
- Research Focus: His research delves into IT strategy, e-commerce, data mining, and big data analytics, exploring the business and social value of technology. His work is published in renowned journals and presented at international conferences.
This unique combination ensures the course content is not only theoretically sound but also grounded in practical, industry-relevant applications.
Course Overview: Objectives and Relevance
The primary objective of this course is to impart knowledge on using advanced data mining techniques to derive actionable business intelligence, ultimately helping organizations achieve their strategic goals.
- Prerequisites: A basic understanding of statistics is required, making it accessible to students from diverse backgrounds.
- Industry Support: The skills taught are in high demand across Big Data companies, Analytics & Consultancy firms, and any corporation with a dedicated Analytics division.
- Key Learning: Participants will learn to build, assess, and compare predictive models using R, working with real datasets and case studies through an easy-to-follow learning curve.
Detailed 12-Week Course Layout
The course is meticulously structured to take you from foundational concepts to advanced modeling techniques.
| Week | Topics Covered |
|---|---|
| Week 1 | General Overview of Data Mining, Data Mining Process, Introduction to R, Basic Statistical Techniques |
| Week 2 & 3 | Data Preparation & Exploration, Visualization Techniques, Dimension Reduction (Principal Component Analysis) |
| Week 4 | Performance Metrics and Assessment for Prediction & Classification |
| Week 5 & 6 | Supervised Learning: Multiple Linear Regression |
| Week 7 | Supervised Learning: Naïve Bayes Classifier |
| Week 8 & 9 | Supervised Learning: Classification & Regression Trees (CART) |
| Week 10 & 11 | Supervised Learning: Logistic Regression, Introduction to Artificial Neural Networks |
| Week 12 | Supervised Learning: Artificial Neural Networks, Discriminant Analysis, Course Conclusion |
Essential Reference Materials
To complement the video lectures and assignments, the course recommends two excellent textbooks that serve as valuable resources during and after your learning journey:
- Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data by EMC Education Services (2015).
- Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner by Shmueli, Patel, & Bruce (2010).
Who Should Enroll?
This course is perfectly suited for:
- Undergraduate & Postgraduate Students in Management Studies, Business Administration, Computer Science, Economics, or Engineering.
- Aspiring Data Analysts & Business Analysts looking to add powerful modeling skills to their toolkit.
- Professionals seeking to transition into analytics roles or leverage data for strategic decision-making.
- Anyone interested in gaining a comprehensive, application-oriented understanding of data mining using the versatile R programming language.
By the end of this 12-week program, you will have a strong command of key data mining methodologies and the practical ability to implement them using R, making you a valuable asset in the burgeoning field of business analytics. Enroll today to transform data into your most strategic business advantage.
Enroll Now →