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About the Coursse
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Artificial Intelligence and Soft Computing :- [Module 1] : Introduction to Artificial Intelligence
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Artificial Intelligence and Soft Computing :- [Module 2] : Problem Solving and Search Techniques
- BFS Algorithm with solved Example
- DFS ( Depth First Search ) Algorithm with solved Example
- IDFS ( Iterative Depth First Search ) Algorithm with solved Example
- GBFS Solved Example
- A star Solved Example
- Hill Climbing
- Hill Climbing algorithm
- Genetic Algorithm
- Genetic Algorithm Max one Problem Solved Example
- Min Max Solved Example
- Alpha-Beta Pruning Solved Example
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Artificial Intelligence and Soft Computing :- [Module 3] : Knowledge Representation, Reasoning
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Artificial Intelligence and Soft Computing :- [Module 4] : Artificial Neural Network
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Artificial Intelligence and Soft Computing :- [Module 5] : Associative Memory Network - Coming Soon
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Artificial Intelligence and Soft Computing :- [Module 6] : Fuzzy System
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Software Engineering [Module 1]:- Introduction To Software Engineering and Process Models
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Software Engineering [Module 2]:- Software Requirements Analysis and Modeling
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Software Engineering [Module 3]:- Software Estimation Metrics
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Software Engineering [Module 4]:- Software Design
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Software Engineering [Module 5]:- Software Testing
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Software Engineering [Module 6]:- Software Configuration Management, Quality Assurance and Maintenance
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Software Engineering [Notes]:- Software Engineering Full Notes
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Software Engineering [Viva Question]:-
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Software Engineering [ Importance ] :-
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Computer Network :- Introduction to Computer Networks
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Computer Network :- Data Link layer
- Framing and it’s Methods
- Error Detection and its Methods
- Hamming Code
- Cyclic Redundancy Check Part [01]
- Cyclic Redundancy Check Part [02]
- Parity Checking and Checksum Error Detection
- Flow Control: Stop and Wait and Sliding Window Protocol
- Go Back- N ARQ System
- SDLC protocol
- HDLC protocol
- CSMA – CD Procedure
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Computer Network :- Network Layer
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Computer Network :- Transport Layer
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Computer Network :- Application Layer
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Computer Network :- Emerging and Advanced Topics
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Computer Network [Notes]:-
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Computer Network [ Importance ] :-
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Computer Network [Viva Questions]:-
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Data Warehouse and Data Mining [Module 1]:- Data Warehousing Fundamentals
- Introduction to Data Warehouse
- Meta Data
- Data Mart
- Data Warehouse Architecture
- How to Draw Star , Smowflake and Fack Constelation Basics
- Numericals on Star , Snowflake and Fact Constelation [ Part 1 ]
- Numericals on Star , Snowflake and Fact Constelation [ Part 2 ]
- What is Olap Operations
- OLAP VS OLTP
- Extract Transform and Load (ETL)
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Data Warehouse and Data Mining [Module 2]:- Introduction to Data Mining, Data Exploration
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Data Warehouse and Data Mining [Module 3]:- Classification
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Data Warehouse and Data Mining [Module 4]:- Clustering
- K Mean clustering with Example [ Type 1 ]
- K Mean clustering with Example [ Type 2 ]
- K Mean Numerical Solved Example [ May 2022 , May 2023 ] [ 10 Marks ] —
- K Medoid with Example
- Agglomerative Clustering Algorithm with Example
- Agglomerative Adjacency Matrix using Euclidean Distance with Solved Example
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Data Warehouse and Data Mining [Module 5]:-Mining frequent patterns and associations
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Data Warehouse and Data Mining [Module 6]:- Web Mining
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Data Warehouse and Data Mining [Notes + Importance Solution]:-
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Data Warehouse and Data Mining [Viva Question]:-
Introduction to Fuzzy Logic
Introduction to Fuzzy Logic
Fuzzy logic is an approach to computing based on “degrees of truth” rather than the usual “true or false” (1 or 0) Boolean logic on which the modern computer is based. The idea of fuzzy logic was first advanced by Lotfi Zadeh of the University of California at Berkeley in the 1960s. Fuzzy Logic is defined as a many-valued logic form that may have truth values of variables in any real number between 0 and 1. It is the handle concept of partial truth. In real life, we may come across a situation where we can’t decide whether the statement is true or false.
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