Sem 5 Comps Bundle [ TCS + DWM + CN + SE ]
₹400,000.00
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Theoretical Computer Science
- 1. Introduction to Finite State Machine-002
- 2. Finite State Machine Problem No. 1-001
- 3. Finite State Machine Problem No. 2-003
- 4. Finite State Machine Problem No. 3-004
- 5. Introduction to Deterministic Finite Automata ( DFA )
- 6. Deterministic Finite Automata ( DFA ) Problem No. 1 ( Updated )
- 7. Deterministic Finite Automata ( DFA ) Problem No. 2
- 8. Deterministic Finite Automata ( DFA ) Problem No. 3
- 9. Deterministic Finite Automata ( DFA ) Problem No. 4
- 10. Regula Expression and Regular Language
- 11. Operations on Language
- 12. Regular Expression to Regular Language
- 13. Regular Language to Regular Expression
- 14. Understanding the flow
- 15. RE to NFA with Epselon Transition using Thompsons COnstruction Method
- 16. RE to NFA with Epselon transition using Thompson’s Construction Method ( Part 2 )
- 17. RLRE to Minimised DFA ( Direct Method )
- 18. RLRE to Minimised DFA ( Imp State Method )
- 19. Convert NFA with E-Transition to NFA without E-Transition
- 20. NFA Without E-Transition to DFA
- 21. Moore & Mealy Machine
- 22. Moore & Mealy Machine ( Problem 1 )
- 23. Introduction to Grammar
- 24. RE – RL to Context Free Grammar
- 25. How to Convert RE RL to Context Free Grammar
- 26. LMD RMD & Parse Tree
- 27. Check whether the given grammar is an ambiguous grammar or not
- 28. Elimination of useless variable
- 29. Elimination of Null Production
- 30. Elimination of unit Production
- 31. Simplification of CFG
- 32. Introduction to Chomsky Normal Form
- 33. CFG to CNF ( Problem No. 1 )-004
- 34. CFG to CNF ( Problem No. 2 )
- 35. CFG to CNF ( Problem No. 3 )-002
- 36. Introduction to Greibach Normal Form ( GNF )
- 37. Convert CFG to GNF ( Problem No. 1 )
- 38. Convert CFG to GNF ( Problem No. 2 )
- 39. Convert CFG to GNF ( Problem No. 3 )
- 40. Convert the following into CNF & GNF
- 41. Introduction to Push Down Automata–
- 42. How to write commands in Push Down Automata–
- 43. Push Down Automata ( Problem No. 1 )–
- 44. Introduction to Turing Machine–
- 45. Convert FA ( DFA ) to PDA–
- 46. Convert CFG to PDA–
- 47. Post Currospondance Problem ( PCP )–
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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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Computer Network [Module 1]:- Introduction to Computer Networks
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Computer Network [Module 2]:-Physical Layer
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Computer Network [Module 3]:- 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
- Carrier Sense Multiple Access-Collision Detection Procedure (CSMA-CD)
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Computer Network [Module 4]:- Network Layer
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Computer Network [Module 5]:- Transport Layer
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Computer Network [Module 6]:- Application Layer
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Computer Network [Module 1]:- Notes: Data Warehousing Fundamentals
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Computer Network [Module 2]:- Notes: Physical Layer
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Computer Network [Module 3]:- Notes: Data Link Layer
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Computer Network [Module 4]:- Notes: Network Layer
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Computer Network [Module 5]:- Notes: Transport Layer
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Computer Network [Module 6]:- Notes: Application Layer
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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]:-
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Data Warehouse and Data Mining [Viva Question]:-
Coming Soon
Course Features
- Lectures 171
- Quizzes 0
- Duration 50 hours
- Skill level All levels
- Language English
- Students 0
- Certificate No
- Assessments Yes