Introduction To Graph

Duration: 5 min

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Module outline

  1. About Course: About the Course
  2. Paper-2 | 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
  3. Paper-2 | Databases / DBMS & SQL: 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
  4. Paper-2 | Algorithms: Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Greedy Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos
  5. Paper-2 | Computer Networks & Security: 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, Hardware Basics, Network Access Technologies, Network Security
  6. Paper-2 | Digital Logic: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Combinational Circuit, Sequential Circuits, Number System, Number Representation, Floating Point Rep
  7. Paper-2 | Operating System: Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Threads & Process Creation, Deadlock, Memory Management, Virtual Memory, Disc Scheduling, File Management
  8. Paper-2 | 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
  9. Paper-2 | Computer Organization & Architecture: Basics of COA, Cache Memory Organization, Input Output Organisation, Pipelining, Instr Formats & Modes, Control Unit Design, Programming the Basic Computer
  10. Paper-2 | 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. Paper-1 | General Awareness: Polity, Physics, Biology, Chemistry, Static General Knowledge, GK- Current Affairs, History, Geography, Indian Economy, Environment
  12. Paper-1 | Logical Reasoning: Series (Number and Letter Series) (Numerical Relations and Reasoning), Coding Decoding, Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning), Data Interpretation, Blood Relations, Syllogisms, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Selection Decision Table (Decision Making), Clock, Calendar, Cubes & Dices, Directions (Direction Test), Analogy, Seating Arrangements, Analytical Reasoning (Counting Figures Reasoning)
  13. Paper-1 | Quantitative Aptitude: Ratio and Proportion (Ratios), Mixture and Alligation, Permutation and Combination, Number System, HCF LCM, Speed Time and Distance, Average, Age Problems, Percentage, Profit and Loss, Time and Work, Pipe and Cistern, Simple Interest and Compound Interest, Powers and Exponents (Surds and Indices), Mensuration and Geometry, Probability, Statistics, Arithmetic, Algebra
  14. Paper-1 | English: Vocabulary, Comprehension / Reading Comprehension / Unseen Passages (Critical Reasoning) (Paragraph Questions), Sentence Re-arrangements (Para Jumbles) (Narrative Sequencing), Sentence Correction (Error Correction), Sentence Completion (Fill in the blanks), Sentence Construction, Cloze Test (Cloze Passage)
  15. Coal India Previous Year Paper:
  16. Engineering Mathematics: Set Theory, Relations, Functions, Graph Theory, Group Theory, Propositional and Predicate Logic, Linear Algebra, Calculus
  17. Coal India Mock Test:
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

The lecture introduces the fundamental definition of a Graph as a data structure composed of two main components: a finite set of vertices (nodes) and a finite set of ordered pairs called edges. The instructor emphasizes that edges are ordered pairs (u, v), meaning the direction matters in directed graphs where (u, v) is distinct from (v, u). He illustrates this with handwritten notes showing arrows and specific examples like (4,1) versus (1,4). The concept of edge weights, values, or costs is introduced, noting that edges can carry numerical data. The session concludes by transitioning to practical applications, highlighting how graphs model real-world networks like city paths, telephone systems, and social media platforms such as Facebook and LinkedIn, where nodes represent entities with attributes like name and gender.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The instructor begins by presenting a slide titled "Graph" which defines the structure. He reads out the two components: "A finite set of vertices also called as nodes" and "A finite set of ordered pair of the form (u, v) called as edge". He underlines these phrases. He explains that the pair is ordered because in a directed graph, (u, v) is not the same as (v, u). Two diagrams are visible on the screen: a complex weighted graph on the left with nodes 0-9 and a simpler unweighted graph on the right with nodes 0-4. He writes "(u, v)" on the screen to represent a generic edge.

  2. 2:00 – 5:00 02:00-05:00

    The instructor elaborates on the concept of ordered pairs to clarify the difference between directed and undirected graphs. He draws an arrow from u to v to visualize directionality. He writes "(4,1)" and "(1,4)" to demonstrate that these are distinct edges in a directed graph, reinforcing the concept of ordering. He underlines "directed graph(di-graph)" and "weight/value/cost". He points to the graph on the left, which has numbers like 4, 11, 8 on the edges, indicating weights. He explains that the pair (u, v) indicates an edge from vertex u to vertex v. He stresses that edges may contain weight, value, or cost, which is a crucial property for algorithms.

  3. 5:00 – 5:30 05:00-05:30

    The slide changes to discuss applications. The text states: "Graphs are used to represent many real-life applications: Graphs are used to represent networks." It lists examples like "paths in a city or telephone network or circuit network". The instructor underlines these terms. He then discusses social networks, specifically mentioning "LinkedIn, Facebook". He explains that in Facebook, "each person is represented with a vertex (or node)". He underlines "structure" and lists node attributes: "person id, name, gender and locale". An image of a highway interchange and a network diagram are shown.

The video provides a foundational overview of Graph theory. It starts with the mathematical definition involving vertices and ordered edges, distinguishing between directed and undirected structures through notation and examples. It then connects these abstract concepts to tangible real-world scenarios, showing how graphs model complex systems ranging from physical infrastructure like telephone networks to digital social connections where nodes hold specific data attributes.

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