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Operating Systems - Computer Science 4

Operating Systems - Computer Science 4


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Last Update 24/02/2022
Completion Time 5 days 7 hours 31 minutes
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Advanced Technical Computer Science Operating Systems
  • Operating systems
    • Introduction to Operating System
    • Basics of OS (Computer System Operation)
    • Basics of OS (Storage Structure)
    • Basics of OS (I/O Structure)
    • Computer System Architecture
    • Operating System Structure
    • Operating System Services
    • User Operating System Interface
    • System Calls
    • Types of System Calls
    • System Programs
    • Operating System Design & Implementation
    • Structures of Operating System
    • Virtual Machines
    • Operating System Generation and System Boot
    • Process Management (Processes and Threads)
    • Process State
    • Process Control Block
    • Process Scheduling
    • Context Switch
    • Operation on Processes – Process Creation
    • Operation on Processes – Process Termination
    • Interprocess Communication
    • Shared Memory Systems
    • Message Passing Systems (Part 1)
    • Message Passing Systems (Part 2)
    • Message Passing Systems (Part 3)
    • Sockets in Operating System
    • Remote Procedure Calls (RPC)
    • Issues in RPC & How They're Resolved
    • Introduction to Threads
    • Multithreading Models & Hyperthreading
    • fork() and exec() System Calls
    • Threading Issues [fork() & exec() System Calls]
    • Threading Issues (Thread Cancellation)
    • Introduction to CPU Scheduling
    • CPU and I/O Burst Cycles
    • Preemptive and Non-Preemptive Scheduling
    • Scheduling Criteria
    • Scheduling Algorithms - First Come First Served (FCFS)
    • First Come First Served Scheduling (Solved Problem 1)
    • First Come First Served Scheduling (Solved Problem 2)
    • Scheduling Algorithms - Shortest Job First (SJF)
    • Shortest Job First Scheduling (Solved Problem 1)
    • Shortest Job First Scheduling (Solved Problem 2)
    • Scheduling Algorithms - Priority Scheduling
    • Priority Scheduling (Solved Problem 1)
    • Priority Scheduling (Solved Problem 2)
    • Scheduling Algorithms - Round Robin Scheduling
    • Round Robin Scheduling (Turnaround Time & Waiting Time)
    • Round Robin Scheduling - Solved Problem (Part 1)
    • Round Robin Scheduling - Solved Problem (Part 2)
    • Multilevel Queue Scheduling Algorithm
    • Multilevel Feedback-Queue Scheduling Algorithm
    • Scheduling Algorithms – Solved Problems
    • Process Synchronization
    • The Critical-Section Problem
    • Peterson’s Solution
      Preview
    • Test and Set Lock
    • Semaphores
    • Disadvantages of Semaphores
    • The Bounded Buffer Problem
    • The Readers Writers Problem
    • The Dining Philosophers Problem
    • Monitors
    • Dining Philosophers Solution using Monitors
    • Process Synchronization - Problem 1
    • Process Synchronization - Problem 2
    • Process Synchronization - Problem 3
    • Process Synchronization - Problem 4
    • Process Synchronization - Problem 5
    • Deadlocks | Chapter-7 | Operating System | nesoacademy.org
    • Main Memory | Chapter-8 | Operating System | nesoacademy.org
    • Virtual Memory | Chapter-9 | Operating System | nesoacademy.org
    • File Systems | Chapter-10 | Operating System | nesoacademy.org
    • File System Implementation | Chapter-11 | Operating System | nesoacademy.org
    • Mass Storage Structure | Chapter-12 | Operating System | nesoacademy.org
    • Lecture 01. Overview (CS 162, Fall 2013, UC Berkeley)
    • Lecture 02. Concurrency Processes, Threads, and Address Spaces (CS 162, Fall 2013, UC Berkeley)
    • Lecture 03. Concurrency and Thread Dispatching (CS 162, Fall 2013, UC Berkeley)
    • Lecture 04. Synchronization, Atomic Operations, Locks (CS 162, Fall 2013, UC Berkeley)
    • Lecture 05. Semaphores, Conditional Variables (CS 162, Fall 2013, UC Berkeley)
    • Lecture 06. Readers:Writers Problem, Working in Teams (CS 162, Fall 2013, UC Berkeley)
    • Lecture 07. Language Support for Concurrent Programming, Deadlocks (CS 162, Fall 2013, UC Berkeley)
    • Lecture 08. Thread Scheduling (CS 162, Fall 2013, UC Berkeley)
    • Lecture 09. Address Translation (CS 162, Fall 2013, UC Berkeley)
    • Lecture 10. Caches and TLBs (CS 162, Fall 2013, UC Berkeley)
    • Lecture 11. Page Allocation and Replacement (CS 162, Fall 2013, UC Berkeley)
    • Lecture 12. Kernel/User, I/O (CS 162, Fall 2013, UC Berkeley)
    • Lecture 13. Disk/SSDs, File Systems (Part 1) (CS 162, Fall 2013, UC Berkeley)
    • Lecture 14. File Systems (Part 2) (CS 162, Fall 2013, UC Berkeley)
    • Lecture 15. Key Value Storage, Network Protocols (CS 162, Fall 2013, UC Berkeley)
    • Lecture 16. Layering (CS 162, Fall 2013, UC Berkeley)
    • Lecture 17. TCP, Flow Control, Reliability (CS 162, Fall 2013, UC Berkeley)
    • Lecture 18. Transactions (CS 162, Fall 2013, UC Berkeley)
    • Lecture 19. Transactions, Two Phase Locking 2PL & Commit 2PC (CS 162, Fall 2013, UC Berkeley)
    • Lecture 20. Why Systems Fail and What We Can Do About It? (CS 162, Fall 2013, UC Berkeley)
    • Lecture 21. Security I: Key Security and Cryptographic Mechanisms (CS 162, Fall 2013, UC Berkeley)
    • Lecture 22. Security II: Host Compromise & Denial of Service (CS 162, Fall 2013, UC Berkeley)
    • Lecture 23. Remote Procedure Call (CS 162, Fall 2013, UC Berkeley)
    • Lecture 24. Capstone: Cloud Computing (CS 162, Fall 2013, UC Berkeley)
  • Artificial intelligence
    • Artificial Intelligence Full Course | Artificial Intelligence Tutorial for Beginners | Edureka
    • 1. Introduction and Scope
    • 2. Reasoning: Goal Trees and Problem Solving
    • 3. Reasoning: Goal Trees and Rule-Based Expert Systems
    • 4. Search: Depth-First, Hill Climbing, Beam
    • 5. Search: Optimal, Branch and Bound, A*
    • 6. Search: Games, Minimax, and Alpha-Beta
    • 7. Constraints: Interpreting Line Drawings
    • 9. Constraints: Visual Object Recognition
    • 10. Introduction to Learning, Nearest Neighbors
    • 11. Learning: Identification Trees, Disorder
    • 12a: Neural Nets
    • 12b: Deep Neural Nets
    • 13. Learning: Genetic Algorithms
    • 14. Learning: Sparse Spaces, Phonology
    • 15. Learning: Near Misses, Felicity Conditions
    • 16. Learning: Support Vector Machines
    • 17. Learning: Boosting
    • 18. Representations: Classes, Trajectories, Transitions
    • 19. Architectures: GPS, SOAR, Subsumption, Society of Mind
    • 21. Probabilistic Inference I
    • 22. Probabilistic Inference II
    • 23. Model Merging, Cross-Modal Coupling, Course Summary
    • Mega-R1. Rule-Based Systems
    • Mega-R2. Basic Search, Optimal Search
    • Mega-R3. Games, Minimax, Alpha-Beta
    • Mega-R4. Neural Nets
    • Mega-R5. Support Vector Machines
    • Mega-R6. Boosting
    • Mega-R7. Near Misses, Arch Learning
  • Software engineering
    • Software Engineering Basics
    • Overview of Software Engineering
    • Software Evolution
    • Software Evolution Laws
    • E-Type Software Evolution
    • Software Paradigms
    • Need of Software Engineering
    • Characteristics of Good Software
    • Software Development Life Cycle
    • Software Development Paradigm
    • Waterfall Model
    • Structured Evolutionary Prototyping Model
    • Incremental Model
    • Rapid Application Development (RAD)
    • Spiral Model
    • V Model
    • Scrum Development Model
    • Big Bang Model
    • Software Project Management
    • Need of Software Project Management
    • Software Project Manager
    • Software Project Management Activities
    • Project Estimation
    • Project Estimation Techniques
    • Project Scheduling
    • Resource Management
    • Project Risk Management
    • Project Execution and Monitoring
    • Project Communication Management
    • Configuration Management
    • Project Management Tools
    • Critical Path Analysis
    • Requirement Engineering Process
    • Requirement Elicitation Techniques
    • Software Requirements
    • User Interface Requirements
    • Software Metrics and Measures
    • Software Design Levels
    • Modularization
    • Cohesion and Coupling
    • Software Quality Attributes
    • Data Flow Diagram
    • Structured Charts
    • HIPO Diagram
    • Structured English
    • Pseudo Code
    • Decision Tables
    • Entity Relationship Model
    • Data Dictionary
    • Structured Design
    • Function Oriented Design
    • Object Oriented Design
    • Software Design Approaches
    • Software User Interface Design
    • Command Line Interface (CLI)
    • Graphical User Interface
    • User Interface Golden Rules
    • Halstead’s Complexity Measures
    • Cyclomatic Complexity Measures
    • Function Point
    • Structured Programming
    • Functional Programming
    • Programming Style
    • Software Documentation
    • Software Validation and Verification
    • Manual Vs Automated Testing
    • Testing Approaches
    • Black Box Testing
    • White Box Testing
    • Testing Levels
    • Testing Documentation
    • Software Maintenance Overview
    • Types of Maintenance
    • Cost of Maintenance
    • Maintenance Activities
    • Software Re engineering
    • Component Reusability
    • CASE Tools
    • Components of CASE Tools
    • Scope of CASE Tools
    • Tutorix Simply Easy Learning Steps
    • Tutorix Brings Simply Easy Learning
    • Tutorix Brings Simply Easy Learning
    • Tutorix Brings Simply Easy Learning
    • UML 2.0 Tutorial
    • UML 2.0 Activity Diagrams
    • UML 2.0 Class Diagrams
    • UML 2 Sequence Diagrams
    • UML 2 Communication Diagrams
    • UML 2 Timing Diagrams
    • UML 2 Component Diagrams
    • UML 2 State Machine Diagrams
    • UML 2 Deployment Diagrams
  • Advanced algorithms
    • Advanced Algorithms (COMPSCI 224), Lecture 1
    • Advanced Algorithms (COMPSCI 224), Lecture 2
    • Advanced Algorithms (COMPSCI 224), Lecture 3
    • Advanced Algorithms (COMPSCI 224), Lecture 4
    • Advanced Algorithms (COMPSCI 224), Lecture 5
    • Advanced Algorithms (COMPSCI 224), Lecture 6
    • Advanced Algorithms (COMPSCI 224), Lecture 7
    • Advanced Algorithms (COMPSCI 224), Lecture 8
    • Advanced Algorithms (COMPSCI 224), Lecture 9
    • Advanced Algorithms (COMPSCI 224), Lecture 10
    • Advanced Algorithms (COMPSCI 224), Lecture 11
    • Advanced Algorithms (COMPSCI 224), Lecture 12
    • Advanced Algorithms (COMPSCI 224), Lecture 13
    • Advanced Algorithms (COMPSCI 224), Lecture 15
    • Advanced Algorithms (COMPSCI 224), Lecture 16
    • Advanced Algorithms (COMPSCI 224), Lecture 17
    • Advanced Algorithms (COMPSCI 224), Lecture 18
    • Advanced Algorithms (COMPSCI 224), Lecture 19
    • Advanced Algorithms (COMPSCI 224), Lecture 20
    • Advanced Algorithms (COMPSCI 224), Lecture 21
    • Advanced Algorithms (COMPSCI 224), Lecture 22
    • Advanced Algorithms (COMPSCI 224), Lecture 23
    • Advanced Algorithms (COMPSCI 224), Lecture 24
    • Advanced Algorithms (COMPSCI 224), Lecture 25
    • Advanced Algorithms (COMPSCI 224), Lecture 26
  • Dynamic programming
    • Dynamic Programming - Learn to Solve Algorithmic Problems & Coding Challenges