Lecture 1 - Introduction to Probability
Lecture 2 - Probability Distributions
Lecture 3 - Probability Distributions and Stochastic Process
Lecture 4 - Parameter Estimation and Software Engineering
Lecture 5 - Software life cycle Model and Concepts of Software Engineering
Lecture 6 - Moduler Design
Lecture 7 - Reliability Theory and its Measures
Lecture 8 - Reliability measures and System Configuration
Lecture 9 - Redundancy in Reliabity
Lecture 10 - Introduction to Software Reliability
Lecture 11 - Software Reliability Measures and Reliability Model Classifications
Lecture 12 - Time between Failure Model
Lecture 13 - Fault Seeding Model and Input Domain Based Model
Lecture 14 - Fault Count Models
Lecture 15 - Markov Models
Lecture 16 - Different Parameters of Musa Execution Time Model and Their Uses
Lecture 17 - Learning Parameter-based Models
Lecture 18 - Models with Fault Dependency and Debugging Time-lag
Lecture 19 - Models with Testing Effort Function
Lecture 20 - Models with Fault Detection, Correction, and Imperfect Debugging Process
Lecture 21 - Important Imperfect Debugging Models
Lecture 22 - Test Coverage Model
Lecture 23 - Discrete Software Reliability Growth Models
Lecture 24 - Change Point-Based Reliability Models
Lecture 25 - Stochastic Software Reliability Models
Lecture 26 - Random Environmental Effect Model
Lecture 27 - Multi Release Software System
Lecture 28 - Software Scheduling
Lecture 29 - Software Release Time Analysis
Lecture 30 - Software Reliability in N Version Programming
Lecture 31 - Time Series based Software Reliability Modesl
Lecture 32 - Important Time Series Based SRGMs
Lecture 33 - Introduction to Fuzzy Set Theory
Lecture 34 - Fuzzy Inference Theorem
Lecture 35 - Soft Computing-Based Optimization Techniques
Lecture 36 - Introduction to Machine Learning Techniques
Lecture 37 - Some Supervised Machine Learning Models
Lecture 38 - Deep Learning Techniques
Lecture 39 - Some Classification Techniques
Lecture 40 - Unsupervised Machine Learning Models
Lecture 41 - Neural Network and Deep Learning-based Reliability Models
Lecture 42 - Early Phase Software Metrics
Lecture 43 - Early Phase Fault Prediction
Lecture 44 - Fault Prone Module Classification Models
Lecture 45 - Deep Learning Models for Module Classification
Lecture 46 - Hybrid Software Classification Models
Lecture 47 - Imbalance Learning Models
Lecture 48 - Transfer Learning-Based Models
Lecture 49 - Unsupervised and Semi-Supervised Fault Prone Module Classification Models
Lecture 50 - Software Dependability Analysis
Lecture 51 - Reqirement Phase Dependability Model
Lecture 52 - Design Phase Dependability Model
Lecture 53 - Tyupe-2 Fuzzy-based Dependability Model
Lecture 54 - Hands-On to Minitab
Lecture 55 - Dependability Model and MATLAB Introduction
Lecture 56 - Software Aging and Rejuvenation
Lecture 57 - Some Aging Models and Software Re-engineering
Lecture 58 - Hands On Python Programming with Libraries
Lecture 59 - Regression and Classification Models (Hands On)
Lecture 60 - Hands-On With Some Machine Learning Models
