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Duration: 7 min

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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.

This educational video demonstrates the application of the Huffman coding algorithm to a set of characters with given probabilities. The instructor guides viewers through the process of generating a Huffman tree, deriving binary codes for each character, and calculating the average number of bits required per character. The lesson covers the step-by-step combination of nodes with the lowest probabilities, the assignment of binary values to tree branches, and the final computation of the weighted path length to determine encoding efficiency.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The lecture begins with the problem statement: "Consider the following character with probability and generate Huffman tree, find Huffman code for each character, find the number of bits required per character?" A table is displayed showing five characters (M1 to M5) with probabilities .12, .04, .45, .17, and .23 respectively. The instructor starts the Huffman algorithm by identifying the two characters with the lowest probabilities, which are M2 (.04) and M1 (.12). He crosses them out and combines them into a new internal node with a probability of 0.16 (0.04 + 0.12). He draws the first part of the tree structure on the whiteboard, showing the parent node 0.16 branching down to M2 and M1. This establishes the foundation for the tree construction.

  2. 2:00 – 5:00 02:00-05:00

    The instructor proceeds to the next step of the algorithm. The remaining probabilities are M3 (.45), M4 (.17), M5 (.23), and the new node (0.16). He sorts these and identifies the two smallest: the node (0.16) and M4 (.17). He combines these to form a new node with probability 0.33. Next, he combines M5 (.23) with the 0.33 node to create a 0.56 node. Finally, he combines M3 (.45) with the 0.56 node to reach the root with probability 1.0. He then assigns binary codes to the branches, marking left branches as 0 and right branches as 1. This results in specific codes: M3 gets '0', M5 gets '10', M4 gets '111', M1 gets '1101', and M2 gets '1100'. The tree is now fully constructed with all leaves labeled.

  3. 5:00 – 7:19 05:00-07:19

    The final phase involves calculating the average number of bits required per character. The instructor writes down the length of the code for each character: M1 has 4 bits, M2 has 4 bits, M3 has 1 bit, M4 has 3 bits, and M5 has 2 bits. He sets up the calculation for the weighted path length: (4 * 0.12) + (4 * 0.04) + (1 * 0.45) + (3 * 0.17) + (2 * 0.23). He computes each term: 0.48, 0.16, 0.45, 0.51, and 0.46. Summing these values, he arrives at a total of 2.06 bits per character, which he writes as the final answer for the average bits required. This calculation demonstrates the efficiency of the Huffman code.

The video effectively connects the theoretical steps of Huffman coding to a practical calculation. By building the tree from the bottom up and assigning codes based on branch paths, the instructor shows how frequent characters get shorter codes. The final calculation of 2.06 bits per character quantifies the compression efficiency achieved by this specific encoding scheme.

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