NPTEL : NOC:Statistical Learning for Reliability Analysis (Computer Science and Engineering)

Co-ordinators : Prof. Monalisa Sarma


Lecture 1 - Introduction to Reliability Engineering

Lecture 2 - Introduction to Statistical Methods in Reliability

Lecture 3 - Concept of Probability and Probability Theory

Lecture 4 - Tutorial on Introduction to RE, SL and Probability Theory - Part I

Lecture 5 - Conditional, Total and Reverse Probability

Lecture 6 - Tutorial on Conditional Probability and Total Probability

Lecture 7 - Introduction to Probability Distributions

Lecture 8 - Introduction to Probability Distributions (Continued...)

Lecture 9 - Discrete Probability Distribution - Part 1

Lecture 10 - Discrete Probability Distribution - Part 2

Lecture 11 - Tutorial on Discrete Probability Distributions

Lecture 12 - Continuous Probability Distributions - Part 1

Lecture 13 - Continuous Probability Distributions - Part 2

Lecture 14 - Tutorial on Continuous Probability Distribution Functions - Part 1

Lecture 15 - Tutorial on Continuous Probability Distribution Functions - Part 2

Lecture 16 - Sampling Distributions - Part 1

Lecture 17 - Sampling Distributions - Part 2

Lecture 18 - Sampling Distributions - Part 3

Lecture 19 - Sampling Distributions - Part 4

Lecture 20 - Sampling Distributions - Part 5

Lecture 21 - Tutorial on Sampling Distributions

Lecture 22 - Statistical Inference - Part 1

Lecture 23 - Statistical Inference - Part 2

Lecture 24 - Statistical Inference - Part 3

Lecture 25 - Tutorial on Statistical Inference

Lecture 26 - Statistical Inference - Part 4

Lecture 27 - Statistical Inference - Part 5

Lecture 28 - Tutorial on Confidence Interval

Lecture 29 - Statistical Inference - Part 6

Lecture 30 - Statistical Inference - Part 7

Lecture 31 - Statistical Inference - Part 8

Lecture 32 - ANOVA - I

Lecture 33 - ANOVA - II

Lecture 34 - ANOVA - III

Lecture 35 - ANOVA - IV

Lecture 36 - ANOVA - V

Lecture 37 - ANOVA - VI

Lecture 38 - Correlation Analysis - Part I

Lecture 39 - Correlation Analysis - Part II

Lecture 40 - Regression Analysis - Part I

Lecture 41 - Regression Analysis - Part II

Lecture 42 - Regression Analysis - Part III

Lecture 43 - Tutorial on Relation Analysis

Lecture 44 - Auto-Regression Analysis

Lecture 45 - Logistic Regression - Part I

Lecture 46 - Logistic Regression - Part II

Lecture 47 - Logistic Regression - Part III

Lecture 48 - Tutorial on Logistic Regression

Lecture 49 - Introduction

Lecture 50 - Bayesian Classification - Part I

Lecture 51 - Bayesian Classification - Part II

Lecture 52 - k-Nearest Neighbor Classification

Lecture 53 - Tutorial on Classification Techniques

Lecture 54 - Support Vector Machine - Part I

Lecture 55 - Support Vector Machine - Part II

Lecture 56 - Support Vector Machine - Part III

Lecture 57 - Support Vector Machine - Part IV

Lecture 58 - Support Vector Machine - Part V

Lecture 59 - Support Vector Machine - Part VI

Lecture 60 - Tutorial on SVM