Course Rationale An introduction to data mining; Data preparation, model building, and data mining techniques such as clustering, decisions trees and neural networks; Induction of predictive models from data: classification, regression, and probability estimation; Application case studies; Data-mining software tools review and comparison.
Course Objectives
Course Outcomes (CO’s)
Topics of Discussion
Expected Learning Outcome
Introduction to Data Mining Lecture Slide
Week 1 Class Recording[Part 1]
Week 1 Class Recording[Part 2]
Week 2 Class Recording
Week 3 Class Recording
Week 4 Class Recording
Week 5 Class Recording[Part1]
Week 5 Class Recording[Part 2]
Week 5 Class recording[Part 3]
Best of Luck!
(2) Write responses in the answer script template either type or hand written
(3) Save the answer script template as pdf e.g. CSE321-N-111-15-1234-mid.pdf (Course Code-Section-Student ID)
During this open book exam, you need to ensure the following items and code of conducts:
(1) No discussion in group or with your classmates as it will be reflected in your answers
(2) No sharing of codes, write-ups or ideas as this will be automatically detected by DIU BLC and will lead to negative marking proposed by the system
Week 9 Class Recording[Part 1]
Week 9 Class Recording[Part 2]
Lesson 1 Lecture Video
Lesson 2 Lecture Video
(3) Save the answer script template as pdf e.g. CSE321-N-111-15-1234-final.pdf (Course Code-Section-Student ID)