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