Estimation Model

Duration: 4 min

This video lesson is available to enrolled students.

Return to /learn/AMCAT-PREPARATION/software-engineering/software-design-estimation-and-metrics/software-project-estimation/asset-estimation-model after enrolling

Inside: a video lesson and guided study material.

Module outline

  1. Quantitative Ability: Percentage, Profit and Loss, Ratio and Proportion (Ratios), Average, Time and Work, Speed Time and Distance, Simple Interest and Compound Interest, Age Problems, Number System, Divisibility Rules, HCF LCM, Algebra, Permutation and Combination, Probability, Data Interpretation, Logarithm, Sequence and Series (Series), Powers and Exponents (Surds and Indices), Speed Mathematics and Basic Mathematics
  2. Logical Reasoning: Seating Arrangements, Puzzle Solving (Puzzles), Data Arrangement, Coding Decoding, Blood Relations, Directions (Direction Test), Ranking, Order and Sequence, Data Sufficiency, Venn Diagram, Inequality, Series (Number and Letter Series) (Numerical Relations and Reasoning), Logical Sequence Of Words, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Selection Decision Table (Decision Making), Analogy, Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning)
  3. Verbal Ability: Comprehension / Reading Comprehension / Unseen Passages (Critical Reasoning) (Paragraph Questions), Subject Verb Agreement (Verb Noun Agreement), Tenses, Articles, Preposition, Conjunction, Modals, Active Passive Voice (Voice), Direct and Indirect Speech, Vocabulary, Sentence Re-arrangements (Para Jumbles) (Narrative Sequencing), Sentence Completion (Fill in the blanks), Sentence Correction (Error Correction), Cloze Test (Cloze Passage), Facts, Inference and Judgements
  4. Programming Fundamentals (Technical): C Fundamentals
  5. Data Structures (Technical): Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing
  6. Algorithms (Technical): Algorithm Analysis, Sorting Algorithms, Greedy Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos, Time Complexity Analysis, Advanced Algorithms
  7. OOPs (Technical): Object Oriented Programming (OOPS)
  8. DBMS (Technical): Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, File Organization & Indexing, Relational Algebra, Relational Calculus, Transaction Management, Concurrency Control, Database Recovery, ORDBMS, Database Security & Authorization, Query Processing & Optimization, Enhanced Data Models, Data Warehousing & Mining, Big Data Systems, NoSQL
  9. SQL (Technical): SQL
  10. Operating Systems (Technical): Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Deadlock, Threads & Process Creation, Memory Management, Virtual Memory, Disc Scheduling, File Management, Windows OS, Linux OS, Security, Distributed Systems, Virtual Machines
  11. Computer Networks (Technical): 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 Security, Cloud Computing and IoT, Cyber and Info Security
  12. Software Engineering (Technical): Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Testing, Software Maintenance and Configuration Management
  13. Coding/Automata Round: Coding Questions by Yash Sir, C Programming by Yash Sir, Programming in C++, Java, Python for Placements by Yash Sir, Pseudo Codes
  14. Personality / Behavioral Assessment: Behavioral Assessment (Behavioral Competency Profiling) (Psychometric Test)
  15. Writing Assessment: English Writing Ability
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

The video is an educational lecture on software engineering estimation models, presented by Sanchit Jain from Knowledge Gate. The lecture begins by introducing the concept of estimation in software development, focusing on two primary metrics: time and cost. It then categorizes estimation into four main types: Post estimation, Base estimation, Decomposition, and Empirical model. The presentation transitions to a specific type, 'Post / Delayed estimation', explaining that this approach is used when dealing with a friendly party and known technology, where the time and cost are not estimated because the cost is expected to be supported in every situation. The video concludes with a 'Thanks for watching' screen.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The video opens with a title card for 'SOFTWARE ENGINEERING' and '#knowledgegate'. It then transitions to a presentation slide titled 'Estimation model'. The slide states that the goal is to estimate time and cost of development. It lists four types of estimation: Post estimation, Base estimation, Decomposition, and Empirical model. A speaker, identified as Sanchit Jain, is visible in a small window, speaking into a microphone. The on-screen text clearly lists the four estimation types, and the speaker's voice explains the concept of estimation in software development.

  2. 2:00 – 3:34 02:00-03:34

    The slide changes to 'Post / Delayed estimation'. The text explains that in the case of a friendly party and known technology, neither time nor cost is estimated because the cost will be supported in every situation. The speaker elaborates on this concept, emphasizing that the relationship with the client and the familiarity with the technology eliminate the need for formal estimation. The on-screen text is clearly visible, and the speaker's voice provides the explanation. The video ends with a final screen that says 'THANKS FOR WATCHING'.

The lecture provides a structured overview of software estimation, starting with a general introduction to the concept and its two key components, time and cost. It then systematically presents four distinct estimation models, with the first being 'Post / Delayed estimation', which is explained as a scenario where estimation is unnecessary due to a pre-existing supportive relationship and technological familiarity. The progression moves from a broad classification to a specific, practical example, illustrating a real-world application of estimation principles.

Loading lesson…