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Course11010411860 lectures

Data Analysis & Decision Making - II

Prof. Raghu Nandan Sengupta · IIT Kanpur

Start with lecture 1 At NPTEL

About

This is the second part of the three part course (DADM-I, DADM-II, DADM-III) which covers Operations Research and its tools with applications. In general Decision Analysis and Decision Making (DADM) covers three main areas which are: Multivariate Statistical Analysis with its applications, Other Decision Making Models like DEA, AHP, ANP, TOPSIS, etc., and Operations Research and its tools with applications. These three part DADM course will be more practical and application oriented rather than theoretical in nature.

Intended audience: Masters in Business Administration, Masters in Economics, Masters in Statistics/Mathematics, Masters in Industrial Engineering, Masters in Operations Research/Operations Management, Phd in related fields as mentioned above.

Prerequisites: Probability & StatisticsOperations Researchl

Lectures

Week 1

  1. Lecture 01: Utility Analysis YouTube
  2. Lecture 02: Utility Analysis YouTube
  3. Lecture 03: Utility Analysis YouTube
  4. Lecture 04: Utility Analysis YouTube
  5. Lecture 05: Utility Analysis YouTube

Week 2

  1. Lecture 06: Utility Analysis YouTube
  2. Lecture 07: Utility anlysis YouTube
  3. Lecture 08: Utility analysis YouTube
  4. Lecture 09: Decisions and Utility Analysis YouTube
  5. Lecture 10: Safety first principle YouTube

Week 3

  1. Lecture 11: Loss Function YouTube
  2. Lecture 12: Loss Function YouTube
  3. Lecture 13: Balanced Loss Function YouTube
  4. Lecture 14: DEA YouTube
  5. Lecture 15: DEA YouTube

Week 4

  1. Lecture 16: DEA YouTube
  2. Lecture 17: DEA YouTube
  3. Lecture 18: Decision Trees YouTube
  4. Lecture 19: Decision Trees YouTube
  5. Lecture 20: Decision Trees YouTube

Week 5

  1. Lecture 21: AHP YouTube
  2. Lecture 22: AHP YouTube
  3. Lecture 23: AHP YouTube
  4. Lecture 24: AHP YouTube
  5. Lecture 25: AHP YouTube

Week 6

  1. Lecture 26: ELECTRE YouTube
  2. Lecture 27: ELECTRE YouTube
  3. Lecture 28: ELECTRE YouTube
  4. Lecture 29: ELECTRE YouTube
  5. Lecture 30: ELECTRE YouTube

Week 7

  1. Lecture 31: TOPSIS YouTube
  2. Lecture 32: TOPSIS YouTube
  3. Lecture 33: TOPSIS YouTube
  4. Lecture 34: TOPSIS YouTube
  5. Lecture 35: TOPSIS YouTube

Week 8

  1. Lecture 36: VIKOR YouTube
  2. Lecture 37: VIKOR YouTube
  3. Lecture 38: VIKOR YouTube
  4. Lecture 39: VIKOR YouTube
  5. Lecture 40: VIKOR YouTube

Week 9

  1. Lecture 41: MAUT YouTube
  2. Lecture 42: MAUT YouTube
  3. Lecture 43: MAUT YouTube
  4. Lecture 44: multi-objective optimization YouTube
  5. Lecture 45: reliability based optimization YouTube

Week 10

  1. Lecture 46: Optimization YouTube
  2. Lecture 47: Goal programming YouTube
  3. Lecture 48: GERT YouTube
  4. Lecture 49: Demand model YouTube
  5. Lecture 50: Bass model YouTube

Week 11

  1. Lecture 51: GERT YouTube
  2. Lecture 52: GERT YouTube
  3. Lecture 53: GERT YouTube
  4. Lecture 54: AIS YouTube
  5. Lecture 55: AIS YouTube

Week 12

  1. Lecture 56: AIS YouTube
  2. Lecture 57: AIS YouTube
  3. Lecture 58: ANN YouTube
  4. Lecture 59: Metaheuristics techniques YouTube
  5. Lecture 60: General Concepts YouTube

Syllabus and materials

At NPTEL, as the course publishes them.

Credits and licence

Institution
IIT Kanpur
Department
Management
Teacher
Prof. Raghu Nandan Sengupta
Level
Undergraduate
Language
English
Subjects
Business and management
Source
NPTEL
Licence
CC BY-NC-SA, as NPTEL states it. Non-commercial use only. NPTEL's terms
Attribution
NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
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