2019(2)

Duration: 3 min

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Inside: a video lesson and guided study material.

Module outline

  1. About the course: About the Course
  2. Mathematical Aptitude: Number System, HCF LCM, Divisibility Rules, Percentage, Ratio and Proportion (Ratios), Average, Profit and Loss, Time and Work, Mensuration and Geometry, Simple Interest and Compound Interest, Speed Time and Distance, Age Problems, Mixture and Alligation, Algebra, Powers and Exponents (Surds and Indices), Pipe and Cistern, Trigonometry, Statistics, Data Interpretation, Arithmetic
  3. Logical Reasoning: Series (Number and Letter Series) (Numerical Relations and Reasoning), Coding Decoding, Analogy, Blood Relations, Directions (Direction Test), Ranking, Order and Sequence, Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning), Seating Arrangements, Syllogisms, Venn Diagram, Puzzle Solving (Puzzles), Logical Sequence Of Words, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Analytical Reasoning (Counting Figures Reasoning), Cubes & Dices, Calendar, Clock
  4. General Knowledge: Physics, Chemistry, Biology, History, Geography, Polity, Indian Economy, GK- Current Affairs, Static General Knowledge
  5. Art of Teaching: Nature, Objectives & Characteristics of Teaching, Learners & Learning Process, Factors Affecting Teaching, Methods of Teaching, Classroom Management & Communication, Teaching-Learning Aids & ICT Integration, Evaluation, Assessment & Measurement, Professional Development & Ethics, Policies, Acts & Contemporary Issues, Curriculum & School Environment, Guidance, Counselling & Mental Health, Inclusive Education & Special Needs, Micro-Teaching & Teaching Skills, Lesson Planning
  6. Environmental Science: Environment
  7. Unit 1 | Digital Electronics: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Combinational Circuit, Sequential Circuits, Number System, Number Representation
  8. Unit 2 | COA: Basics of COA, Floating Point Rep, Cache Memory Organization, Input Output Organisation, Instr Formats & Modes, Control Unit Design, Register Transfer and Microoperations, Programming the Basic Computer
  9. Unit 3 | C Programming: C Fundamentals, Control Flow, Functions, Arrays & Pointers, Storage Classes, Structures & Enums, DMA, Macros, Scoping & File Handling
  10. Unit 3 | Data Structures: Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing
  11. Unit 4 | Algorithms: Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos, Advanced Algorithms
  12. Unit 5 | Operating System: Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Threads & Process Creation, Deadlock, Memory Management, Virtual Memory, Disc Scheduling, File Management
  13. Unit 6 | Database Management System: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, File Organization & Indexing, Relational Algebra, SQL, Transaction Management, Concurrency Control
  14. Unit 7 | Computer Networks: Introduction to CN, Data Communication, DLL: Access Control, DLL: Flow Control, DLL: Error Control, DLL: Framing, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Net Layer:Routing Protocol, Transport Layer Services, TL: Congestion & UDP, Application Layer
  15. Unit 8 | Software Engineering: Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Testing, Software Maintenance and Configuration Management
  16. Unit 9 | Object Oriented Programming: OOPS with C++
  17. Unit 10 | Web Development: HTML Basics, CSS, JavaScript-Basics, XML
  18. Unit 11 | Theory Of Computation: Introduction to TOC, Deterministic FA (DFA), Non-Deterministic FA, Regular Expressions, Grammar, Regular Language Properties, Moore & Mealy Machines, Pushdown Automata & CFG, Turing Machines
  19. Unit 12 | IoT: Emerging Tech Trends, Cloud Computing
  20. Unit 13 | Artificial Intelligence: Approaches to AI, Search Algorithms, Game Playing, Knowledge Representation, Natural Language Processing, Artificial Neural Networks, Genetic Algorithms
  21. Unit 14 | E-Commerce: Electronic Data Interchange and E-Commerce, Role of Internet and Web Services, Security in Mobile and Wireless Computing, Physical Security and Cryptography Basics, Cyber Safety and Security
  22. Unit 15 | Multimedia: Multimedia
  23. Unit 16 | Python: Introduction to Python, Tokens, Variables, Data Types, I/O, Operators & Expressions, Control Flow & Looping, Collections & Strings, Functions & Modules, File Handling & Data Analysis, DSA using Python
  24. Full Length Mock Tests — General Paper:
  25. Full Length Mock Tests — Computer Science (Paper II):
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

The video presents a multiple-choice question from the GATE 2019 exam about Dijkstra's algorithm. The instructor analyzes each of the four options to determine which statement is not true. He confirms that options (A), (B), and (D) are true: Dijkstra's algorithm can find the shortest path within the same graph data structure, it always selects the node with the smallest known distance, and it requires non-negative edge weights. He then focuses on option (C), which states that the shortest path always passes through the least number of vertices. To disprove this, he draws a graph with vertices S, A, B, C, and D, and demonstrates that the shortest path from S to D (S->A->B->D with a total cost of 8) is not the path with the fewest vertices (S->C->D with a cost of 9). This counterexample shows that the shortest path is based on minimizing total weight, not the number of vertices, making (C) the correct answer to the question.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The video begins with a question displayed on screen: 'When using Dijkstra's algorithm to find shortest path in a graph, which of the following statement is not true? (NET 2019 DEC)'. The four options are listed: (A) It can find shortest path within the same graph data structure, (B) Every time a new node is visited, we choose the node with smallest known distance/cost to visit first, (C) Shortest path always passes through least number of vertices, and (D) The graph needs to have a non-negative weight on every edge. The instructor, visible in the bottom right, begins to analyze the options. He marks (A) as true, explaining that the algorithm operates on the graph itself. He marks (B) as true, stating that the core of Dijkstra's algorithm is to always pick the node with the minimum distance. He then marks (D) as true, noting that negative weights can cause the algorithm to fail. He then focuses on option (C), which he identifies as the incorrect statement, and begins to explain why.

  2. 2:00 – 2:38 02:00-02:38

    The instructor draws a graph on the screen to provide a counterexample for option (C). The graph has vertices S, A, B, C, and D. The edges are S->A (weight 1), A->B (weight 1), B->D (weight 6), S->C (weight 2), and C->D (weight 7). He calculates the cost of the path S->A->B->D as 1+1+6=8. He calculates the cost of the path S->C->D as 2+7=9. He concludes that the shortest path from S to D is S->A->B->D, which has 3 vertices (A, B, D). The path S->C->D has only 2 vertices (C, D), which is fewer. Since the shortest path does not pass through the least number of vertices, the statement in (C) is false. He marks (C) as 'false' and confirms it is the correct answer to the question.

The video systematically evaluates four statements about Dijkstra's algorithm. It confirms that the algorithm operates on the same graph, always selects the node with the minimum known distance, and requires non-negative edge weights. The key insight is that the algorithm's goal is to minimize the total path weight, not the number of vertices. The instructor uses a clear counterexample to demonstrate that a path with a lower total weight can have more vertices than a path with a higher total weight, thereby proving that the shortest path does not necessarily pass through the least number of vertices. This logical disproof identifies (C) as the only false statement.

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