Understanding How Computers Work

Introduction to CPUs

CPUs (Central Processing Units) are pieces of silicon with billions of microscopic switches called transistors.
Transistors function like light bulbs: on (1) or off (0), representing binary states.
Bit: Value at one transistor; Byte: Group of 8 bits, capable of 256 combinations.
Computers use binary (base-2) to store information; Hexadecimal (base-16) is more human-readable.

Using transistors to create logic gates that perform calculations based on Boolean algebra (binary).
ASCII: Character encoding translating binary to human-readable characters.
Operating systems (Windows, Linux, Mac) manage hardware and applications.

RAM (Random Access Memory): Essential for the CPU’s operation, storing data or instructions.
Machine cycle: CPU fetches, decodes, executes, and stores information.
CPU clock speed measured in GHz; multiple cores mean handling instructions in parallel.

Shell: Program exposing the kernel for user commands.
Programming Languages: Abstract machine code; compiled (C) or interpreted (Python).
- Variables assign values to names; data types include characters, integers, and floating points.

Pointers: Variables storing memory addresses; Pointer arithmetic allows navigating memory.
Manual memory management in languages like C (allocation, freeing) vs. garbage collection in higher-level languages like Python.
Arrays and Linked Lists: Data structures with different memory utilization and flexibility.

Stacks (LIFO) and Queues (FIFO): Fundamental data structures for task organization.
Hash Maps: Key-value pairs, dealing with collisions via linked lists.
Graphs and Trees: Nodes connected by edges, useful for network analysis and hierarchies.
Binary Search Trees: Fast data retrieval by node comparison.

Functions: Implement algorithms, taking inputs and returning outputs.
Recursion: Functions calling themselves with a base condition to stop infinite loops.
Memoization: Storing past results to avoid redundant calculations.
Big O Notation: Describes time/space complexity for growth trends in algorithms.
Search Algorithms: Brute force vs. divide and conquer (e.g., binary search).
Programming Paradigms: Declarative vs. imperative vs. object-oriented programming.

Training algorithms on data for tasks without explicit programming.
Neural Networks: Algorithms adjusting parameters to improve task accuracy over time.

Physical hardware: global network of cables and ISPs.
IP addresses and TCP: Ensuring data transmission.
HTTP and URLs: Protocol for web communication. Browsers request web content using DNS and receive responses.
HTML, CSS, JavaScript: Structure, style, and functionality of web pages.
HTTP response codes indicate status (200 OK, 404 Page Not Found).
APIs: Allow interaction between applications via HTTP methods (GET, POST, PUT, DELETE).  Relational Databases: Tables, columns, rows, primary and foreign keys, SQL for data manipulation.

SQL Injection Attacks: Vulnerabilities in user input validation can lead to unauthorized database access.

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