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About the Coursse 0
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Artificial Intelligence and Soft Computing :- [Module 1] : Introduction to Artificial Intelligence 7
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Introduction to Artificial Intelligence 40 minLecture2.1
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Agent and Peas Description 08 minLecture2.2
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Types of Agent 09 minLecture2.3
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Learning Agent 09 minLecture2.4
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Introduction to soft computingLecture2.5
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Soft vs Hard Computing 10 minLecture2.6
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Learning and its Types 07 minLecture2.7
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Artificial Intelligence and Soft Computing :- [Module 2] : Problem Solving and Search Techniques 11
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BFS Algorithm with solved Example 06 minLecture3.1
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DFS ( Depth First Search ) Algorithm with solved Example 03 minLecture3.2
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IDFS ( Iterative Depth First Search ) Algorithm with solved Example 03 minLecture3.3
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GBFS Solved Example 08 minLecture3.4
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A star Solved Example 14 minLecture3.5
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Hill Climbing 04 minLecture3.6
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Hill Climbing algorithm 06 minLecture3.7
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Genetic Algorithm 06 minLecture3.8
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Genetic Algorithm Max one Problem Solved Example 09 minLecture3.9
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Min Max Solved Example 07 minLecture3.10
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Alpha-Beta Pruning Solved Example 14 minLecture3.11
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Artificial Intelligence and Soft Computing :- [Module 3] : Knowledge Representation, Reasoning 7
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Propositional Logic (PL) Introduction 08 minLecture4.1
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PL to CNF Conversion With Solved Example 10 minLecture4.2
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First-Order Logic (FOL) Solved Example 06 minLecture4.3
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Resolution Tree Sum Part #1 09 minLecture4.4
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Resolution Tree Sum Part #2 15 minLecture4.5
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Forward Chaining Criminal Numerical 18 minLecture4.6
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Backward Chaining Criminal Numerical 11 minLecture4.7
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Artificial Intelligence and Soft Computing :- [Module 4] : Artificial Neural Network 8
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Neural Network & Types 21 minLecture5.1
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Introduction to ANN and Structure (Components) of Ann 05 minLecture5.2
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Mc Culloch Pitts Neuron Model 02 minLecture5.3
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Neural Network Architecture 04 minLecture5.4
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Perceptron Learning 10 minLecture5.5
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Activation Functions 04 minLecture5.6
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Back Propogations Network with Solved Example 18 minLecture5.7
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Self Organizing Maps and KSOMS 10 minLecture5.8
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Artificial Intelligence and Soft Computing :- [Module 5] : Associative Memory Network - Coming Soon 0
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Artificial Intelligence and Soft Computing :- [Module 6] : Fuzzy System 7
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FUZZY LOGICLecture7.1
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Introduction to Fuzzy Logic 04 minLecture7.2
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Fuzzification and De-Fuzzification 06 minLecture7.3
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Properties and Operation of Crisp and Fuzzy Sets 05 minLecture7.4
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Crisp and Fuzzy Sets and Relations 11 minLecture7.5
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Mamdani Model 33 minLecture7.6
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Fuzzy Inference System 06 minLecture7.7
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Software Engineering [Module 1]:- Introduction To Software Engineering and Process Models 10
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Introduction to Software Engineering 10 minLecture8.1
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Process Framework Model 07 minLecture8.2
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Capability Maturity Model (CMM) 09 minLecture8.3
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Waterfall Model 07 minLecture8.4
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Iterative Model 06 minLecture8.5
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Agile Development Process 10 minLecture8.6
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Extreme Programming 13 minLecture8.7
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Schedule Slippage and Cost Slippage 03 minLecture8.8
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SCRUM 09 minLecture8.9
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Verification and Validation 03 minLecture8.10
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Software Engineering [Module 2]:- Software Requirements Analysis and Modeling 4
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Data Flow Diagram 29 minLecture9.1
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SRS 15 minLecture9.2
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SRS Example 18 minLecture9.3
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SRS Characteristics 07 minLecture9.4
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Software Engineering [Module 3]:- Software Estimation Metrics 2
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Cocomo Model (Constructive Cost Model Introduction) 07 minLecture10.1
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Software measurement and Function Point Analysis 06 minLecture10.2
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Software Engineering [Module 4]:- Software Design 6
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Cohesion and Coupling 09 minLecture11.1
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Use Case Diagram 14 minLecture11.2
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Class diagram 20 minLecture11.3
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Sequence diagram 17 minLecture11.4
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Component diagram 06 minLecture11.5
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Deployment diagram 09 minLecture11.6
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Software Engineering [Module 5]:- Software Testing 6
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Integration Testing 04 minLecture12.1
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Object-Oriented Testing 05 minLecture12.2
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White Box Testing 16 minLecture12.3
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Black Box Testing 12 minLecture12.4
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Reverse Engineering 04 minLecture12.5
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Alpha and Beta Testing 03 minLecture12.6
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Software Engineering [Module 6]:- Software Configuration Management, Quality Assurance and Maintenance 8
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Software Configuration Management 09 minLecture13.1
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Risk Identification 05 minLecture13.2
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RMMM ( Risk Mitigation Monitoring Management ) 03 minLecture13.3
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Version Control 03 minLecture13.4
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Change Control 04 minLecture13.5
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Formal Technical Review (FTR) 08 minLecture13.6
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Maintenance in Software Engineering 04 minLecture13.7
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Service-Oriented Software Engineering 06 minLecture13.8
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Software Engineering [Notes]:- Software Engineering Full Notes 1
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Software Engineering Full NotesLecture14.1
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Software Engineering [Viva Question]:- 6
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Introduction to Software Engineering and Process ModelsLecture15.1
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Software Requirements Analysis and ModelingLecture15.2
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Software Estimation MetricsLecture15.3
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Software DesignLecture15.4
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Software TestingLecture15.5
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Software Configuration Management, Quality Assurance and MaintenanceLecture15.6
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Software Engineering [ Importance ] :- 7
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Introduction To SE and Process ModelsLecture16.1
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Software Req Analysis and ModelingLecture16.2
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Software Estimation MetricsLecture16.3
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Software DesignLecture16.4
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Software TestingLecture16.5
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SCM, QA and MaintenanceLecture16.6
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[Extra] Previously Asked Important QuestionsLecture16.7
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Computer Network :- Introduction to Computer Networks 9
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Introduction to Computer Networks 12 minLecture17.1
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Network Topologies Types 12 minLecture17.2
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Network Connecting Devices 11 minLecture17.3
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Connection-Oriented vs Connection-Less Communication 09 minLecture17.4
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OSI Reference Model 07 minLecture17.5
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TCP-IP Reference Model 07 minLecture17.6
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OSI vs TCP-IP 08 minLecture17.7
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Network Classification LAN, MAN, WAN 08 minLecture17.8
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Virtual LAN 08 minLecture17.9
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Computer Network :- Data Link layer 11
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Framing and it’s Methods 08 minLecture18.1
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Error Detection and its Methods 08 minLecture18.2
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Hamming Code 10 minLecture18.3
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Cyclic Redundancy Check Part [01] 09 minLecture18.4
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Cyclic Redundancy Check Part [02] 05 minLecture18.5
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Parity Checking and Checksum Error Detection 09 minLecture18.6
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Flow Control: Stop and Wait and Sliding Window Protocol 08 minLecture18.7
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Go Back- N ARQ System 08 minLecture18.8
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SDLC protocol 05 minLecture18.9
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HDLC protocol 12 minLecture18.10
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CSMA – CD Procedure 07 minLecture18.11
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Computer Network :- Network Layer 8
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IP address vs MAC address 09 minLecture19.1
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IPv4 Header Format 13 minLecture19.2
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IPv4 vs IPv6 10 minLecture19.3
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Routing Algorithms Part 01 12 minLecture19.4
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Routing Algorithms Part 02 10 minLecture19.5
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ARP & RARP 07 minLecture19.6
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Leaky Bucket Algorithm 05 minLecture19.7
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Token Bucket Algorithm 06 minLecture19.8
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Computer Network :- Transport Layer 3
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Berkeley Sockets 07 minLecture20.1
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User Datagram Protocol 08 minLecture20.2
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Multiplexing 07 minLecture20.3
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Computer Network :- Application Layer 4
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Domain Name Server – DNS 06 minLecture21.1
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Simple Mail Transfer Protocol – SMTP 05 minLecture21.2
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Hypertext Transfer Protocol – HTTP 08 minLecture21.3
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File Transfer Protocol – FTP 05 minLecture21.4
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Computer Network :- Emerging and Advanced Topics 3
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VPN (Virtual Private Networks) 06 minLecture22.1
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SDN (Software Defined Networks) 08 minLecture22.2
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SDN – Open flow Protocols 07 minLecture22.3
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Computer Network [Notes]:- 10
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Introduction To NetworkingLecture23.1
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Physical LayerLecture23.2
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Data Link LayerLecture23.3
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Network LayerLecture23.4
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Transport LayerLecture23.5
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Application LayerLecture23.6
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IPv4 & IPv6Lecture23.7
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Cyclic Redundancy SumsLecture23.8
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Error Hamming SumLecture23.9
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Medium Access Control Sublayer [Extra]Lecture23.10
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Computer Network [ Importance ] :- 7
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Introduction To NetworkingLecture24.1
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Physical LayerLecture24.2
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Data Link LayerLecture24.3
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Network LayerLecture24.4
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Transport LayerLecture24.5
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Application LayerLecture24.6
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[Extra] Previously Asked Important QuestionsLecture24.7
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Computer Network [Viva Questions]:- 6
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Physical LayerLecture25.1
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IntroductionLecture25.2
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Data Link LayerLecture25.3
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Network layerLecture25.4
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Transport LayerLecture25.5
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Application LayerLecture25.6
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Data Warehouse and Data Mining [Module 1]:- Data Warehousing Fundamentals 10
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Introduction to Data Warehouse 11 minLecture26.1
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Meta Data 05 minLecture26.2
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Data Mart 06 minLecture26.3
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Data Warehouse Architecture 07 minLecture26.4
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How to Draw Star , Smowflake and Fack Constelation Basics 10 minLecture26.5
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Numericals on Star , Snowflake and Fact Constelation [ Part 1 ] 16 minLecture26.6
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Numericals on Star , Snowflake and Fact Constelation [ Part 2 ] 11 minLecture26.7
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What is Olap Operations 08 minLecture26.8
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OLAP VS OLTP 08 minLecture26.9
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Extract Transform and Load (ETL) 09 minLecture26.10
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Data Warehouse and Data Mining [Module 2]:- Introduction to Data Mining, Data Exploration 7
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Introduction to Data Mining and Architecture 10 minLecture27.1
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KDD Process in Data Mining 09 minLecture27.2
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Types of Attribute 09 minLecture27.3
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Data Visualization Part #1 11 minLecture27.4
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Data Visualization Part #2 11 minLecture27.5
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Data Preprocessing Part #1 17 minLecture27.6
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Data Preprocessing Part #2 09 minLecture27.7
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Data Warehouse and Data Mining [Module 3]:- Classification 5
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Naive Bayes Numerical Solved Example [ Nov 2022 ] [ 10 Marks ]– 12 minLecture28.1
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Naive Bayes Part #1 18 minLecture28.2
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Naive Bayes Part #2 25 minLecture28.3
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Decision Tree 24 minLecture28.4
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Performance Evaluation metrics 23 minLecture28.5
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Data Warehouse and Data Mining [Module 4]:- Clustering 6
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K Mean clustering with Example [ Type 1 ] 12 minLecture29.1
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K Mean clustering with Example [ Type 2 ] 23 minLecture29.2
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K Mean Numerical Solved Example [ May 2022 , May 2023 ] [ 10 Marks ] — 11 minLecture29.3
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K Medoid with Example 21 minLecture29.4
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Agglomerative Clustering Algorithm with Example 13 minLecture29.5
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Agglomerative Adjacency Matrix using Euclidean Distance with Solved Example 05 minLecture29.6
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Data Warehouse and Data Mining [Module 5]:-Mining frequent patterns and associations 2
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Apiori Algoirthm with Solved Example 12 minLecture30.1
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FP Tree Algorithm with Solved Example 15 minLecture30.2
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Data Warehouse and Data Mining [Module 6]:- Web Mining 4
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Web content mining 06 minLecture31.1
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Web Mining 07 minLecture31.2
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Page rank Algorithm 06 minLecture31.3
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HITTS Algorithm [ Hubs and Authority ] 12 minLecture31.4
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Data Warehouse and Data Mining [Notes + Importance Solution]:- 6
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Data warehouse and Data Mining ImportanceLecture32.1
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Naive Bayes Numerical Solved ExampleLecture32.2
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K Mean Numerical Solved ExampleLecture32.3
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Star and Snowflake Schema NumericalsLecture32.4
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Data Warehouse and Data Mining NOTESLecture32.5
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Data Warehouse and Data Mining ImportanceLecture32.6
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Data Warehouse and Data Mining [Viva Question]:- 6
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IntroductionLecture33.1
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Introduction to Data Mining,Data Exploration and Data Pre-processingLecture33.2
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ClusteringLecture33.3
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ClassificationLecture33.4
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Mining frequent patterns and associationsLecture33.5
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Web MiningLecture33.6
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