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Modulewise Importance 2026 5
- Lecture2.1
  
  DAV IMP 2026
- Lecture2.2
  
  CSS IMP 2026
- Lecture2.3
  
  ML IMP 2026
- Lecture2.4
  
  DC Imp 2026
- Lecture2.5
  
  SEPM IMP 2026
[ SEPM ] [Module 1]:- Introduction To Software Engineering and Process Models 10
- Lecture3.1
  
  Introduction to Software Engineering 10 min
- Lecture3.2
  
  Process Framework Model 07 min
- Lecture3.3
  
  Capability Maturity Model (CMM) 09 min
- Lecture3.4
  
  Waterfall Model in Soft Development Life cycle 07 min
- Lecture3.5
  
  Agile Development Process 10 min
- Lecture3.6
  
  Schedule Slippage and Cost Slippage 03 min
- Lecture3.7
  
  Extreme Programming (XP) in SDLC 13 min
- Lecture3.8
  
  SCRUM 09 min
- Lecture3.9
  
  Iterative Model in SDLC 06 min
- Lecture3.10
  
  Verification and Validation 03 min
[ SEPM ] [Module 2]:- Requirements Analysis and Cost Estimation 5
- Lecture4.1
  
  SRS 15 min
- Lecture4.2
  
  SRS Example 18 min
- Lecture4.3
  
  SRS Characteristics 07 min
- Lecture4.4
  
  Cocomo Model (Constructive Cost Model Introduction) 07 min
- Lecture4.5
  
  Process and Project Matrices SP Estimation 06 min
[ SEPM ] [Module 3]:- Software Risk and Configuration Management 8
- Lecture5.1
  
  Risk Identification 05 min
- Lecture5.2
  
  RMMM ( Rish Mitigation Monitoring Management ) 03 min
- Lecture5.3
  
  Change Control 04 min
- Lecture5.4
  
  Version Control 03 min
- Lecture5.5
  
  Formal Technical Review (FTR) 08 min
- Lecture5.6
  
  Maintenance in Software Engineering 04 min
- Lecture5.7
  
  Service-Oriented Architecture 06 min
- Lecture5.8
  
  Software Configuration Management 09 min
[ SEPM ] [Module 4]:- Software Testing and Maintenance 6
- Lecture6.1
  
  Integration Testing 04 min
- Lecture6.2
  
  Object-Oriented 05 min
- Lecture6.3
  
  White Box Testing 16 min
- Lecture6.4
  
  Black Box Testing 12 min
- Lecture6.5
  
  Reverse Engineering 04 min
- Lecture6.6
  
  Alpha and Beta testing 03 min
[ SEPM ] IT Project Management and Project Scheduling 4
- Lecture7.1
  
  Introduction To Project Management 10 min
- Lecture7.2
  
  W5HH PRINCIPLE 12 min
- Lecture7.3
  
  PMBOK 12 min
- Lecture7.4
  
  Risk Categorization 13 min
[SEPM] - Importance Solutions Notes - Modulewise 6
- Lecture8.1
  
  Module 1
- Lecture8.2
  
  Module 2
- Lecture8.3
  
  Module 3
- Lecture8.4
  
  Module 4
- Lecture8.5
  
  Module 5
- Lecture8.6
  
  Module 6
[ SEPM ] Software Engineering Importance (OLD) 7
- Lecture9.1
  
  Introduction To SE and Process Models
- Lecture9.2
  
  Software Req Analysis and Modeling
- Lecture9.3
  
  Software Estimation Metrics
- Lecture9.4
  
  Software Design
- Lecture9.5
  
  Software Testing
- Lecture9.6
  
  SCM, QA and Maintenance
- Lecture9.7
  
  [Extra] Previously Asked Important Questions
[ SEPM ] Software Engineering Viva Question 6
- Lecture10.1
  
  Introduction to Software Engineering and Process Models
- Lecture10.2
  
  Software Requirements Analysis and Modeling
- Lecture10.3
  
  Software Estimation Metrics
- Lecture10.4
  
  Software Design
- Lecture10.5
  
  Software Testing
- Lecture10.6
  
  Software Configuration Management, Quality Assurance and Maintenance
[ SEPM ] Software Engineering Notes 2
- Lecture11.1
  
  Software Engineering Sample Notes
- Lecture11.2
  
  Software Engineering Full Notes
[ ML ] [Module 1]:- Introduction to Machine Learning 5
- Lecture12.1
  
  Introduction to Machine Learning 13 min
- Lecture12.2
  
  Key point in Machine Learning 10 min
- Lecture12.3
  
  Steps in Machine learning 05 min
- Lecture12.4
  
  Issue in Machine Learning 07 min
- Lecture12.5
  
  Module 1 Notes
[ ML ] [Module 2]:- Mathematical Foundation for ML 2
- Lecture13.1
  
  Matrix Diagonalization 26 min
- Lecture13.2
  
  Numericals on SVD 25 min
[ ML ] [Module 3]:- Linear Models 4
- Lecture14.1
  
  Linear Regression 09 min
- Lecture14.2
  
  Support Vector Machine 10 min
- Lecture14.3
  
  Linear Regression Numerical ML 09 min
- Lecture14.4
  
  Least Square Regression Numerical ML 09 min
[ ML ] [Module 4]:- Clustering 2
- Lecture15.1
  
  Hebbian Learning 12 min
- Lecture15.2
  
  Expectation Maximization Algorithm 06 min
[ ML ] [Module 5]:- CLassification 9
- Lecture16.1
  
  Neural Network 18 min
- Lecture16.2
  
  Artificial Neural Network 16 min
- Lecture16.3
  
  Logistic Regression #1 09 min
- Lecture16.4
  
  Logistic Regression #2 14 min
- Lecture16.5
  
  Perceptron-Model 13 min
- Lecture16.6
  
  Error-Back-Propogation 14 min
- Lecture16.7
  
  Multi-Layer-Perceptron-Model 16 min
- Lecture16.8
  
  Activation-Function 13 min
- Lecture16.9
  
  Delta-Learning-Rule 15 min
[ ML ] [Module 6]:- Dimensionality Reduction 4
- Lecture17.1
  
  PCA (Principal component Analysis ) Concept 14 min
- Lecture17.2
  
  Dimensionality Reduction 08 min
- Lecture17.3
  
  PCA (Principal Component Analysis) Sum 19 min
- Lecture17.4
  
  Module 6 Notes
[ML] Notes + IMP Soln 2025 6
- Lecture18.1
  
  Module 1 – Introduction to Machine Learning
- Lecture18.2
  
  Module 2 – Mathematical Foundations for Machine Learning
- Lecture18.3
  
  Module 3 – Linear Models
- Lecture18.4
  
  Module 4 – Clustering
- Lecture18.5
  
  Module 5 – Classification Models
- Lecture18.6
  
  Module 6 – Dimensionality Reduction
[ CNS ] Module 01:- Introduction to Network Security & Cryptography 11
- Lecture19.1
  
  Introduction to Cryptography and Security System 09 min
- Lecture19.2
  
  Security Goals and Mechanism 10 min
- Lecture19.3
  
  Symmetric Cipher 02 min
- Lecture19.4
  
  Mono Alphabetic Cipher 08 min
- Lecture19.5
  
  Poly Alphabetic Cipher 07 min
- Lecture19.6
  
  Substitution Cipher 14 min
- Lecture19.7
  
  Transposition Cipher 07 min
- Lecture19.8
  
  Euler’s Phi Function
- Lecture19.9
  
  HILL-CIPHER PYQ 19 min
- Lecture19.10
  
  Steganography 11 min
- Lecture19.11
  
  Playfair-Cipher- numerical PYQ 24 min
[ CNS ] Module 02:- Block Cipher and Public Key Cryptography 11
- Lecture20.1
  
  Block Cipher and Modes of Block Cipher Part 1 20 min
- Lecture20.2
  
  Block Cipher and Modes of Block Cipher Part 2 18 min
- Lecture20.3
  
  Stream and Block Cipher 04 min
- Lecture20.4
  
  Modes of Operation 08 min
- Lecture20.5
  
  DES Algorithm Full Working 12 min
- Lecture20.6
  
  DES key Generation Explain Step by Step 11 min
- Lecture20.7
  
  AES Algorithm Full working 26 min
- Lecture20.8
  
  Public Key cryptogrpahy 03 min
- Lecture20.9
  
  RSA Algorithm with Solved Example 14 min
- Lecture20.10
  
  Diffie Hellman 07 min
- Lecture20.11
  
  How to find modulus of Exponential Number (high power value ) 12 min
[ CNS ] Module 03:- Cryptographic Hashes, Message Digests - Digita 6
- Lecture21.1
  
  Hash-Function & its Properties 13 min
- Lecture21.2
  
  MD5 (Message Digest Algorithm) 24 min
- Lecture21.3
  
  SHA-1 Algorithm Full Working 23 min
- Lecture21.4
  
  MAC 07 min
- Lecture21.5
  
  Digital Certificate 10 min
- Lecture21.6
  
  X.509 Digital Certificate 21 min
[ CNS ] Module 04:- Digital Signature Schemes & Authentication 4
- Lecture22.1
  
  Authentication-Protocol 13 min
- Lecture22.2
  
  Digital Signature Full working Explained 19 min
- Lecture22.3
  
  Needam Schroeder Protocol 22 min
- Lecture22.4
  
  RSA Algorithm with Solved Example 19 min
[ CNS ] Module 05:-M5 - System Security 5
- Lecture23.1
  
  Memory & Address Protection Part-2 19 min
- Lecture23.2
  
  Memory & Address Protection Part-1 15 min
- Lecture23.3
  
  FIle Protection 10 min
- Lecture23.4
  
  Database Security 13 min
- Lecture23.5
  
  Multilevel Database Security 12 min
[ CNS ] Module 6 - Web Security 6
- Lecture24.1
  
  Session Hijacking 25 min
- Lecture24.2
  
  Firewall & types 19 min
- Lecture24.3
  
  SSL ( Secure Socket Layer protocol ) 17 min
- Lecture24.4
  
  Penetration Testing 17 min
- Lecture24.5
  
  Web-Security 14 min
- Lecture24.6
  
  Web-Browser Attack 16 min
[ CSS ] Notes + IMP 7
- Lecture25.1
  
  Cryptography and System Security Importance 2025
- Lecture25.2
  
  M1 – Introduction to Number Theory
- Lecture25.3
  
  M2- Block Ciphers & Public Key Cryptography
- Lecture25.4
  
  M3 – Cryptographic Hashes, Message Digests and Digital Certificates
- Lecture25.5
  
  M4- Digital Signature Schemes and Authentication Protocols
- Lecture25.6
  
  M5- System Security
- Lecture25.7
  
  M6- Web Security
[ DAV ] [ Module 1 ] : Introduction to Data Analytics and Lifecycle 1
- Lecture26.1
  
  Introduction to Data Analytics and LifeCycle 21 min
[ DAV ] [ Module 2 ] : Regression Model 3
- Lecture27.1
  
  Numericals on Regression Part-2 17 min
- Lecture27.2
  
  Numericals on Regression Part-1 22 min
- Lecture27.3
  
  Numericals on Regression Part-3 18 min
[ DAV ] [ Module 3 ] : Time Series Analysis 4

Coming Soon
- Lecture28.1
  
  Time Series Analysis Its Components 14 min
- Lecture28.2
  
  Box Jenkins Intervention Analysis 13 min
- Lecture28.3
  
  ARIMA-Model-and-Its-Pros-&-Cons 13 min
- Lecture28.4
  
  Difference-Between-ARMA-&-ARIMA 12 min
[ DAV ] [ Module 4 ] : Text Analytics 2
- Lecture29.1
  
  Explain Steps of Text Analysis 15 min
- Lecture29.2
  
  Seven Practice Areas of Text Analytics 13 min
[ DAV ] [ Module 5 ] : Data analytics and visualization with R 12
- Lecture30.1
  
  Introduction – R Programming – #1 12 min
- Lecture30.2
  
  Introduction – R Programming – #2 16 min
- Lecture30.3
  
  Vectors in R Programming 17 min
- Lecture30.4
  
  Objects in R Programming 18 min
- Lecture30.5
  
  Interacting With Users 12 min
- Lecture30.6
  
  Script in R 13 min
- Lecture30.7
  
  Plot in R 17 min
- Lecture30.8
  
  Exploring Dataset in R 25 min
- Lecture30.9
  
  Dirty Data Detection In Exploration Phase 21 min
- Lecture30.10
  
  Data import and export in R 32 min
- Lecture30.11
  
  Visualization in R 16 min
- Lecture30.12
  
  Function in R 12 min
[ DAV ] Notes 6
- Lecture31.1
  
  Module 1
- Lecture31.2
  
  Module 2
- Lecture31.3
  
  Module 3
- Lecture31.4
  
  Module 4
- Lecture31.5
  
  Module 5
- Lecture31.6
  
  Module 6
[ DAV ] Module wise Imp 3
- Lecture32.1
  
  Cryptography and System Security Sem 6 AIML
- Lecture32.2
  
  Machine Learning Importance Modulewise 2025
- Lecture32.3
  
  DAV Importance Modulewise 2025
[ DC ] [ Module 1 ] : Introduction to Distributed System 7
- Lecture33.1
  
  Introduction to Distributed System 11 min
- Lecture33.2
  
  World Wide Web 09 min
- Lecture33.3
  
  Issues and Goals 13 min
- Lecture33.4
  
  System Model ( Architecture Model ) 10 min
- Lecture33.5
  
  System Model (Fundamental Model ) 12 min
- Lecture33.6
  
  Software Concepts Models of DS 06 min
- Lecture33.7
  
  Client Server Model 11 min
[ DC ] [ Module 2 ] : Communication 4
- Lecture34.1
  
  RPC Remote Procedure Call in Distributed System 07 min
- Lecture34.2
  
  RMI Remote Method Invocation 07 min
- Lecture34.3
  
  Stream-Oriented Communication 08 min
- Lecture34.4
  
  Stream oriented vs Message Oriented 07 min
[ DC ] [ Module 3 ] : Synchronization 12
- Lecture35.1
  
  Synchronization in Process Distribution System 05 min
- Lecture35.2
  
  Cristian algorithm 05 min
- Lecture35.3
  
  Berkeley Algorithm in Hindi in Process Distribution System 04 min
- Lecture35.4
  
  Network Time Protocol 05 min
- Lecture35.5
  
  Logical Clock in Distributed System 06 min
- Lecture35.6
  
  Lamport’s Logical clock Algorithm in Distributed System 05 min
- Lecture35.7
  
  Lam-ports Non Token Based Algorithm in Mutual Execution 09 min
- Lecture35.8
  
  Vector Logical Clock Algorithm 07 min
- Lecture35.9
  
  Ricart Agrawala Algorithm 07 min
- Lecture35.10
  
  Suzuki Kasami Algorithm with Example 09 min
- Lecture35.11
  
  Raymonds Algorithm 05 min
- Lecture35.12
  
  Bully and Ring Election algorithm in Distributed System 10 min
[ DC ] [ Module 4 ] : Resource and Process Management 6
- Lecture36.1
  
  Resources management in Distributed System 07 min
- Lecture36.2
  
  Desirable features of Global scheduling Algorithm 12 min
- Lecture36.3
  
  Load Balancing Algorithm and Design Issues 16 min
- Lecture36.4
  
  Load Balancing by Harsh 14 min
- Lecture36.5
  
  Load Balancing vs Load Sharing 04 min
- Lecture36.6
  
  Load Sharing Algorithm with Design issues 12 min
[ DC ] [ Module 5 ] : Consistency, Replication and Fault Tolerance 2
- Lecture37.1
  
  Data-Centric Consistency Model 18 min
- Lecture37.2
  
  Client-Centric Consistency Model 09 min
[ DC ] [ Module 6 ] : Distributed File Systems and Name Services 9
- Lecture38.1
  
  Introduction to Distributed File System 12 min
- Lecture38.2
  
  Good features of Distributed File System 11 min
- Lecture38.3
  
  File Accessing Models 13 min
- Lecture38.4
  
  File Replication 11 min
- Lecture38.5
  
  Introduction to network file system 08 min
- Lecture38.6
  
  Network file system Full concept 30 min
- Lecture38.7
  
  AFS 09 min
- Lecture38.8
  
  Hadoop Distributed File System 05 min
- Lecture38.9
  
  File Cache Scheme 10 min
[ DC ] Notes 6
- Lecture39.1
  
  Module 1
- Lecture39.2
  
  Module 2
- Lecture39.3
  
  Module 3
- Lecture39.4
  
  Module 4
- Lecture39.5
  
  Module 5
- Lecture39.6
  
  Module 6
[ DC ] [Extra Notes] 3
- Lecture40.1
  
  Distributed System Introduction
- Lecture40.2
  
  Communication Notes
- Lecture40.3
  
  Synchronization
[DC] IMP 1
- Lecture41.1
  
  IMP

Alpha and Beta testing

Alpha and Beta testing in software Engineering

Alpha Testing is a type of software testing performed to identify bugs before releasing the product to real users or to the public. Beta Testing is performed by real users of the software application in a real environment. Beta testing is one of the type of User Acceptance Testing.

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Course Overview 0

This Course is Only Available On Our App

Modulewise Importance 2026 5

[ SEPM ] [Module 1]:- Introduction To Software Engineering and Process Models 10

[ SEPM ] [Module 2]:- Requirements Analysis and Cost Estimation 5

[ SEPM ] [Module 3]:- Software Risk and Configuration Management 8

[ SEPM ] [Module 4]:- Software Testing and Maintenance 6

[ SEPM ] IT Project Management and Project Scheduling 4

[SEPM] - Importance Solutions Notes - Modulewise 6

[ SEPM ] Software Engineering Importance (OLD) 7

[ SEPM ] Software Engineering Viva Question 6

[ SEPM ] Software Engineering Notes 2

[ ML ] [Module 1]:- Introduction to Machine Learning 5

[ ML ] [Module 2]:- Mathematical Foundation for ML 2

[ ML ] [Module 3]:- Linear Models 4

[ ML ] [Module 4]:- Clustering 2

[ ML ] [Module 5]:- CLassification 9

[ ML ] [Module 6]:- Dimensionality Reduction 4

[ML] Notes + IMP Soln 2025 6

[ CNS ] Module 01:- Introduction to Network Security & Cryptography 11

[ CNS ] Module 02:- Block Cipher and Public Key Cryptography 11

[ CNS ] Module 03:- Cryptographic Hashes, Message Digests - Digita 6

[ CNS ] Module 04:- Digital Signature Schemes & Authentication 4

[ CNS ] Module 05:-M5 - System Security 5

[ CNS ] Module 6 - Web Security 6

[ CSS ] Notes + IMP 7

[ DAV ] [ Module 1 ] : Introduction to Data Analytics and Lifecycle 1

[ DAV ] [ Module 2 ] : Regression Model 3

[ DAV ] [ Module 3 ] : Time Series Analysis 4

[ DAV ] [ Module 4 ] : Text Analytics 2

[ DAV ] [ Module 5 ] : Data analytics and visualization with R 12

[ DAV ] Notes 6

[ DAV ] Module wise Imp 3

[ DC ] [ Module 1 ] : Introduction to Distributed System 7

[ DC ] [ Module 2 ] : Communication 4

[ DC ] [ Module 3 ] : Synchronization 12

[ DC ] [ Module 4 ] : Resource and Process Management 6

[ DC ] [ Module 5 ] : Consistency, Replication and Fault Tolerance 2

[ DC ] [ Module 6 ] : Distributed File Systems and Name Services 9

[ DC ] Notes 6

[ DC ] [Extra Notes] 3

[DC] IMP 1

Alpha and Beta testing

Alpha and Beta testing in software Engineering

Alpha Testing is a type of software testing performed to identify bugs before releasing the product to real users or to the public. Beta Testing is performed by real users of the software application in a real environment. Beta testing is one of the type of User Acceptance Testing.

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