This course aims to provide a solid understanding of Data Analytics theory and applications in business. The course will, first, cover the mathematical underpinnings and scientific concepts that are necessary for building robust Data Analytics models. Secondly, various well-established algorithms and techniques will be introduced. The course will also discuss recent progress made by the scientific and technical community in the field of Data Science by drawing examples from various case studies, existing datasets and journal articles. Associate shall get a hands-on experience in the application of these techniques for addressing practical problems from the retail domain, through a hands-on project. Course material will be containing coding examples in R derived from various case studies.
1. Broad understanding of basic theory underlying Data Analytics learning.
2. Understanding the appropriateness of a learning technique for a given business case along with its strength and limitations.
3. Ability to match existing business problems to standard Data Modeling practices.
4. Ability to apply learning algorithms to solve business problems, through hands-on project.
Basic understanding of R, a free software environment, available for Unix, Windows and MacOS.
1. Basic Understanding of Probability and Statistics.
2. Matrix Algebra and Optimization.
3. Online Lectures ( http://nptel.ac.in/courses/110105060/)
o Sampling distribution
o Hypothesis testing
o Multivariate descriptive statistics
o Multivariate normal distribution