Computer Systems Basics

Computer Systems

• A computer is a programmable electronic device that can store, process, and communicate information.
• Fixed computers perform a specific task and cannot be changed, whereas programmable computers can be programmed to perform different tasks.
• Calculators are specialized computers designed for mathematical calculations, whereas computers are general-purpose devices.
• Input devices: keyboard, mouse, scanner, etc.
• Output devices: monitor, printer, speaker, etc.

RAM vs ROM

• RAM (Random Access Memory) is a volatile memory that temporarily stores data and program instructions, allowing the CPU to access and process them quickly.
• ROM (Read-Only Memory) is a non-volatile memory that permanently stores data and program instructions, which cannot be changed by the user.

Secondary Storage

• Secondary storage is necessary to store large amounts of data permanently, even when the power is turned off.
• Types of secondary storage: Hard Disk Drive (HDD), Solid-State Drive (SSD), Flash Drive, CD, DVD, Blu-ray.
• Magnetic technology uses magnetic fields to store data on disks, optical technology uses light to store data on discs, and solid-state technology uses flash memory to store data.

CPU

• The CPU (Central Processing Unit) is the brain of the computer, executing instructions and performing calculations.
• Parts of the CPU: ALU (Arithmetic Logic Unit), Busses, Clock, Registers, Control Unit.

Operating System

• The operating system manages computer resources, providing a platform for running application software.
• Roles of the operating system: Managing Memory, Program execution, Managing Input and Output, Managing User Interface (GUI), Managing Communication.

Binary

• Binary is a number system that uses only two digits: 0 and 1.
• To convert Denary to Binary, divide the number by 2 and note the remainders.
• To convert Binary to Denary, multiply each digit by the corresponding power of 2 and add them up.

Data Sizes

• Bit: the smallest unit of data, representing a single binary digit.
• Nibble: a group of 4 bits.
• Byte: a group of 8 bits, representing a single character.
• Kilobyte (KB): 1024 bytes.
• Megabyte (MB): 1024 KB.
• Gigabyte (GB): 1024 MB.
• Terabyte (TB): 1024 GB.

Algorithms, Computational Thinking, and Introduction to Python

• Computational Thinking: a problem-solving approach that involves abstraction, decomposition, pattern recognition, and algorithmic thinking.
• Abstraction: focusing on essential features while ignoring irrelevant details.
• Decomposition: breaking down complex problems into smaller, manageable parts.
• Pattern recognition: identifying patterns and relationships in data.
• Algorithm: a step-by-step procedure for solving a problem.

Representing Algorithms

• Flowcharts: a graphical representation of an algorithm using shapes and symbols.
• Correct use of shapes in flowcharts: rectangles for processes, diamonds for decisions, and triangles for input/output.
• Creating a flowchart for an algorithm: identify inputs, processes, and outputs.

Python Programming

• Sequence: the order of steps in a program or algorithm.
• Selection: using if-else statements to make decisions based on conditions.
• Iteration: repeating a sequence of steps using while loops or for loops.
• Variables: storing and changing values in a program.
• Data Types: integers, floats, strings, booleans, etc.
• Casting: converting data types during input.

AI Experience

• AI (Artificial Intelligence): the development of computer systems that can perform tasks that typically require human intelligence.
• Types of AI: Machine Learning, Narrow AI, General AI.
• Machine Learning: a type of AI that enables computers to learn from data without being explicitly programmed.
• Types of machine learning: Supervised, Unsupervised, Reinforcement, Semi-supervised.

AI Lifecycle

• Defining the problem: identifying a problem or opportunity for AI to solve.
• Preparing Data: collecting, cleaning, and preprocessing data for machine learning.
• Training: using machine learning algorithms to train a model on prepared data.
• Testing: evaluating the performance of the trained model on new data.
• Evaluating the Model: measuring the accuracy and confidence of the model.

Machine Learning: Data Preparation (Cleaning)

• Duplicates: removing duplicate data points to prevent bias.
• Missing data: handling missing values to prevent errors.
• Invalid data: detecting and removing invalid or corrupted data.

Machine Learning: Testing

• Testing for Bias: evaluating the model for bias and fairness.
• Measuring accuracy and confidence: evaluating the model's performance using metrics such as precision, recall, and F1 score.

Decision Trees

• Decision trees: a machine learning model that uses a tree-like structure to classify data.
• How decision trees are made: recursively partitioning data into smaller subsets based on features.
• Solving problems with ML models: using decision trees to solve classification problems.

Computer Systems

• A computer is a programmable electronic device that can store, process, and communicate information.
• Fixed computers perform a specific task and cannot be changed, whereas programmable computers can be programmed to perform different tasks.
• Calculators are specialized computers designed for mathematical calculations, whereas computers are general-purpose devices.
• Input devices: keyboard, mouse, scanner, etc.
• Output devices: monitor, printer, speaker, etc.

RAM vs ROM

• RAM (Random Access Memory) is a volatile memory that temporarily stores data and program instructions, allowing the CPU to access and process them quickly.
• ROM (Read-Only Memory) is a non-volatile memory that permanently stores data and program instructions, which cannot be changed by the user.

Secondary Storage

• Secondary storage is necessary to store large amounts of data permanently, even when the power is turned off.
• Types of secondary storage: Hard Disk Drive (HDD), Solid-State Drive (SSD), Flash Drive, CD, DVD, Blu-ray.
• Magnetic technology uses magnetic fields to store data on disks, optical technology uses light to store data on discs, and solid-state technology uses flash memory to store data.

CPU

• The CPU (Central Processing Unit) is the brain of the computer, executing instructions and performing calculations.
• Parts of the CPU: ALU (Arithmetic Logic Unit), Busses, Clock, Registers, Control Unit.

Operating System

• The operating system manages computer resources, providing a platform for running application software.
• Roles of the operating system: Managing Memory, Program execution, Managing Input and Output, Managing User Interface (GUI), Managing Communication.

Binary

• Binary is a number system that uses only two digits: 0 and 1.
• To convert Denary to Binary, divide the number by 2 and note the remainders.
• To convert Binary to Denary, multiply each digit by the corresponding power of 2 and add them up.

Data Sizes

• Bit: the smallest unit of data, representing a single binary digit.
• Nibble: a group of 4 bits.
• Byte: a group of 8 bits, representing a single character.
• Kilobyte (KB): 1024 bytes.
• Megabyte (MB): 1024 KB.
• Gigabyte (GB): 1024 MB.
• Terabyte (TB): 1024 GB.

Algorithms, Computational Thinking, and Introduction to Python

• Computational Thinking: a problem-solving approach that involves abstraction, decomposition, pattern recognition, and algorithmic thinking.
• Abstraction: focusing on essential features while ignoring irrelevant details.
• Decomposition: breaking down complex problems into smaller, manageable parts.
• Pattern recognition: identifying patterns and relationships in data.
• Algorithm: a step-by-step procedure for solving a problem.

Representing Algorithms

• Flowcharts: a graphical representation of an algorithm using shapes and symbols.
• Correct use of shapes in flowcharts: rectangles for processes, diamonds for decisions, and triangles for input/output.
• Creating a flowchart for an algorithm: identify inputs, processes, and outputs.

Python Programming

• Sequence: the order of steps in a program or algorithm.
• Selection: using if-else statements to make decisions based on conditions.
• Iteration: repeating a sequence of steps using while loops or for loops.
• Variables: storing and changing values in a program.
• Data Types: integers, floats, strings, booleans, etc.
• Casting: converting data types during input.

AI Experience

• AI (Artificial Intelligence): the development of computer systems that can perform tasks that typically require human intelligence.
• Types of AI: Machine Learning, Narrow AI, General AI.
• Machine Learning: a type of AI that enables computers to learn from data without being explicitly programmed.
• Types of machine learning: Supervised, Unsupervised, Reinforcement, Semi-supervised.

AI Lifecycle

• Defining the problem: identifying a problem or opportunity for AI to solve.
• Preparing Data: collecting, cleaning, and preprocessing data for machine learning.
• Training: using machine learning algorithms to train a model on prepared data.
• Testing: evaluating the performance of the trained model on new data.
• Evaluating the Model: measuring the accuracy and confidence of the model.

Machine Learning: Data Preparation (Cleaning)

• Duplicates: removing duplicate data points to prevent bias.
• Missing data: handling missing values to prevent errors.
• Invalid data: detecting and removing invalid or corrupted data.

Machine Learning: Testing

• Testing for Bias: evaluating the model for bias and fairness.
• Measuring accuracy and confidence: evaluating the model's performance using metrics such as precision, recall, and F1 score.

Decision Trees

• Decision trees: a machine learning model that uses a tree-like structure to classify data.
• How decision trees are made: recursively partitioning data into smaller subsets based on features.
• Solving problems with ML models: using decision trees to solve classification problems.

This quiz covers the fundamental concepts of computer systems, including types of computers, input and output, memory, secondary storage, and CPU components. Test your understanding of the basics of computer systems!