Operating Systems - Computer Science 4
Responsible | Lorcan Camps |
---|---|
Last Update | 24/02/2022 |
Completion Time | 5 days 7 hours 31 minutes |
Members | 3 |
Share This Course
Share Link
Share on Social Media
Share by Email
Please login to share this Operating Systems - Computer Science 4 by email.
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
-
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
-