2019(2)

Duration: 3 min

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Inside: a video lesson and guided study material.

Module outline

  1. General Intelligence & Reasoning: Analogy, Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning), Series (Number and Letter Series) (Numerical Relations and Reasoning), Coding Decoding, Blood Relations, Directions (Direction Test), Ranking, Order and Sequence, Logical Sequence Of Words, Syllogisms, Venn Diagram, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Selection Decision Table (Decision Making), Data Sufficiency, Puzzle Solving (Puzzles), Data Arrangement, Cubes & Dices, Calendar, Clock, Arithmetic, Number System, HCF LCM, Verbal Analogy (Word Based Analogy), Visual Recognition and Figure Completion, Paper Folding and Cutting, Transformation of Shapes, Clocks and Calendars, Direction Sense, Cubes and Dice, Patterns in Two-Dimensional Figures, Seating Arrangements, Analogy and Classification, Logical Deduction and Induction, Alphabet and Word Tests, Mathematical Operations, Series Completion, Simplification and Approximation, Coding and Decoding, Numerical Reasoning, Assembling and Grouping of Shapes, Three-Dimensional Patterns and Visualization, Vocabulary, Number System, Averages, Mixtures and Alligation, Simple and Compound Interest, Percentages, Algebra, Speed, Time and Distance, Seating and Arrangement Puzzles, Traverse Surveying, Order, Ranking and Sequence, Constraint Puzzles, Syllogisms and Venn Diagrams, Reading Comprehension, Critical Reasoning, Permutations and Combinations, Narrative Sequencing, Project Monitoring, Resources and Safety, Profit, Loss and Discount, Ratio and Proportion, Time and Work, Mensuration, Data Interpretation, Powers, Surds and Logarithms, Sequences and Series, Articles and Determiners, Sentence Completion, Data Sufficiency, Blood Relations, Simple Interest and Compound Interest, Mixture and Alligation, Sequence and Series (Series), Speed Time and Distance, Algebra, Profit and Loss, Powers and Exponents (Surds and Indices), Permutation and Combination
  2. General Awareness: Physics, Chemistry, Biology, History, Geography, Polity, Indian Economy, Environment, Static General Knowledge, GK- Current Affairs, Artificial Intelligence, MS Office Applications, Terms & Abbreviations, Keyboard Shortcuts, Evolution of Indian Banking (Banking & Financial Awareness), Emerging Tech Trends
  3. Engineering Mathematics: Set Theory, Relations, Functions, Graph Theory, Group Theory, Propositional and Predicate Logic, Linear Algebra, Calculus, Probability, Statistics, Signal Space and Optimum Detection, Probability, Statistics
  4. Digital Logic: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Combinational Circuit, Sequential Circuits, Number System, Number Representation, Floating Point Rep, Number Systems and Codes, Registers and Counters, Boolean Algebra and Logic Gates, Microprocessors and Microcontrollers, Logic Families and CMOS Logic, Microprocessors, Logic Gates and Boolean Algebra, Minimization of Boolean Functions, Timing, Hazards and Testing, Logic Families, Combinational Logic Design, Arithmetic Circuits, Waveform Generators and Timer Circuits, Semiconductor Memories and Programmable Logic Devices, Combinational Logic Circuits, Latches and Flip-Flops, Finite State Machines, Sequential Circuits and State Machines, Minimization of Boolean Functions, Arithmetic Circuits, Latches and Flip-Flops, Number Systems and Codes, Registers and Counters
  5. Computer Organisation & Architecture: Basics of COA, Cache Memory Organization, Input Output Organisation, Pipelining, Instr Formats & Modes, Control Unit Design, Programming the Basic Computer, Register Transfer and Microoperations, Semiconductor Memories and Programmable Logic, Processor Organization and Instructions, Memory Hierarchy and Input/Output, Registers and Counters
  6. Programming & Data Structures: C Fundamentals, Control Flow, Functions, Arrays & Pointers, Storage Classes, Structures & Enums, DMA, Macros, Scoping & File Handling, Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing, HTML Basics, OOPS with C++, Java, Object Oriented Technology
  7. Databases: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, File Organization & Indexing, Relational Algebra, SQL, Relational Calculus, Transaction Management, Concurrency Control, Database Recovery, Database Security & Authorization
  8. Algorithms: Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Greedy Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos
  9. 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, Complexity Theory
  10. Compiler Design: Intro to Compilers, Lexical Analysis, Grammar & CFG, Syntax Analysis: Top-Down, Syntax Analysis: Bottom-Up, Semantic Analysis & SDT, Intermediate Code Gen, Code Optimization, Run Time Environment
  11. Operating System: Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Threads & Process Creation, Deadlock, Memory Management, Virtual Memory, Disc Scheduling, File Management, Security, Windows OS, Distributed Systems, Unix OS, Linux OS
  12. Computer Networks: Introduction to CN, 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, Hardware Basics, Data Communication, Website, Browser & Services, Web Design & Development, Network Security, Cyber Threats and Malware Attacks, Cyber Safety and Security
  13. Full Length Mock Tests:
  14. Sectional Tests:
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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