Exam Preparation PDF
ABOUT THE COURSE: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 computing software) to build, assess, and compare models based on real datasets and cases with an easy-to-follow learning curve.
INTENDED AUDIENCE: UG & PG engineering students: all branches, MBA students, Professionals working in or aspiring for Business Analyst, Data Analyst, Data Scientist, and Data Engineer roles
PREREQUISITES: Business Analytics & Data Mining Modeling Using R
INDUSTRY SUPPORT: Big Data companies, Analytics & Consultancy companies, Companies with Analytics Division
Summary
| Course Status : | Ongoing |
| Course Type : | Elective |
| Duration : | 4 weeks |
| Category : |
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| Credit Points : | 1 |
| Level : | Undergraduate/Postgraduate |
| Start Date : | 24 Jul 2023 |
| End Date : | 18 Aug 2023 |
| Enrollment Ends : | 07 Aug 2023 |
| Exam Registration Ends : | 21 Aug 2023 |
| Exam Date : | 24 Sep 2023 IST |
Course layout
Week 1 : Unsupervised Learning Methods : Association Rules
Week 2 : Unsupervised Learning Methods : Cluster Analysis
Week 3 : Time Series Forecasting: Understanding Time Series and Regression-Based Forecasting Methods
Week 4 : Time Series Forecasting: Smoothing Methods and Conclusion
Week 2 : Unsupervised Learning Methods : Cluster Analysis
Week 3 : Time Series Forecasting: Understanding Time Series and Regression-Based Forecasting Methods
Week 4 : Time Series Forecasting: Smoothing Methods and Conclusion
Books and references
1. Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data by EMC Education Services (2015)
2. Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner by Shmueli, G., Patel, N. R., & Bruce, P. C. (2010)
Exam Preparation PDF
Part : 1Part : 2
Part : 3
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