Data Warehousing and Data Mining (Machine Learning)

Perquisites:

Programming and Data Structures, Database Management System and Linear Algebra.

Course Objective(s):

1. To understand classical models and algorithms in data warehousing and data mining.

2. To enable students to analyze the data, identify the problems, and choose the relevant models and algorithms to apply.

3. To assess the strengths and weaknesses of various methods and algorithms and to analyze their behavior.

Course Outcomes:

On completion of the course students will be able to

CO1: Understand Data Mining Fundamentals and remember the various issues in Data mining.

CO2: Understand and give examples of Data warehousing & it’s different tools and analyze Business problems in real applications in industry.

CO3: Apply and analyze the basic of machine learning techniques and its various types along with the description of association and regression.

CO4: Develop the concept of the classification and clustering algorithms in machine learning.