Base Estimation

Duration: 2 min

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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, specifically focusing on the concept of 'Base estimation'. The presentation begins with a title card for 'SOFTWARE ENGINEERING' and '#knowledgegate'. The main content is a slide titled 'Base estimation' which defines the term as a method to predict the cost and time of an entire project based on experience from previous projects. The instructor, Sanchit Jain, is visible in a small window, speaking into a microphone and explaining the concept. The video concludes with a 'THANKS FOR WATCHING' screen. The entire presentation is copyrighted content from Knowledge Gate Eduventures.

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 'Base estimation'. The slide contains a bullet point defining the concept: 'In base estimation we predict the cost and time of the entire project based on the experience which we have gained from the previous projects.' The instructor, Sanchit Jain, is visible in a small window in the bottom right, speaking into a microphone. A watermark at the bottom of the screen states, 'THIS IS A COPYRIGHTED CONTENT OF KNOWLEDGE GATE EDUVENTURES.' The instructor's voice explains the definition provided on the slide, emphasizing that this method relies on historical data from past projects to forecast future project timelines and budgets.

  2. 2:00 – 2:14 02:00-02:14

    The video concludes with a final screen displaying the text 'THANKS FOR WATCHING' in large, white capital letters against a dark, abstract background with blue and gold digital lines. Below this, the hashtag '#knowledgegate' is visible. This screen serves as an outro, signaling the end of the lecture on base estimation.

The video provides a concise, lecture-style explanation of 'Base estimation' in software engineering. It begins with a title card, moves to a slide that defines the concept as a predictive method using past project experience, and features an instructor explaining the definition. The lesson is self-contained, focusing solely on this one estimation technique. The video concludes with a standard 'Thanks for watching' message, indicating the end of the educational segment.

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