Computer Science 101

Introduction to Computer Science

• When facing a code error:
  • First Step: Change nothing, try running it again.
  • If unsuccessful: Might feel like you need a Computer Science degree.
  • Irony: High-paying jobs in software engineering without knowing how things work feel like magic.

Understanding Computers

• Turing Machine: A theoretical device that manipulates symbols on a strip of tape according to a table of rules and can compute anything.
• Central Processing Unit (CPU): Contains a piece of silicon with billions of transistors acting as switches.
• Bit: Smallest piece of information a computer can use; a value at a switch.
• Byte: A package of 8 bits; can represent 256 different values.
• Character Encoding: Characters typed are mapped to binary values (e.g., ASCII, UTF-8).

Binary and Hexadecimal Systems

• Binary System: Uses 0 and 1; difficult for humans to read.
• Hexadecimal System: Base 16 format, representing binary in a more readable form.
• Nibble: A 4-bit group in hexadecimal.

Programming and Machine Code

• Programming Languages: Code in higher-level languages is converted to machine code (binary format).
• Random Access Memory (RAM): Stores data for applications; each location has a memory address.

Computing Hardware

• Input Devices: Keyboard, mouse.
• Output Devices: Monitor.
• Operating Systems (OS): Provide an interface for managing hardware resources (e.g., Linux, Windows).
• Shell: A program that exposes the OS to the user, taking text input and producing output; can connect to remote computers via SSH.

Programming Languages and Abstractions

• Scripting Languages: Python (interpreted line by line).
• Compiled Languages: C++ (compiled into machine code before execution).
• Built-in Data Types: Characters, numbers, variables.
• Dynamic Typing: Python automatically identifies data types.
• Static Typing: In languages like C, data types must be specified.
• Memory Management: Allocation and deallocation of memory.
• Garbage Collection: Automatic memory management.

Data Types and Structures

• Integers and Floats: Whole numbers and numbers with decimals.
• Characters and Strings: Individual characters or sequences.
• Big Endian vs. Little Endian: Memory storage order.

Data Structures

• Array/List: Indexed collection starting at 0.
• Linked List: Items pointing to the next item.
• Stack: Last in, first out (LIFO).
• Queue: First in, first out (FIFO).
• Hash/Map/Dictionary: Key-value pairs.
• Trees: Hierarchical data structure.
• Graphs: Nodes connected in various ways.

Algorithms

• Function: Block of code taking input, processing, and outputting a result.
• Conditional Logic: If-else statements.
• Loops: Repeating blocks of code (for, while).
• Recursion: Function calling itself; needs a base condition to avoid infinite loops.
• Big-O Notation: Measures algorithm performance (time and space complexity).
• Common Algorithms:
  • Brute Force: Trying all possible combinations.
  • Divide and Conquer: Splitting problems into smaller parts.
  • Dynamic Programming: Using memoization to store sub-problem results.
  • Greedy Algorithms: Short-term beneficial choices.
  • Backtracking Algorithms: Incremental exploration of paths.

Programming Paradigms

• Declarative Programming: Describes what the program does, not how.
• Imperative Programming: Explicit instructions for control flow.
• Multi-Paradigm Languages: Support multiple programming styles (e.g., Python, JavaScript).
• Object-Oriented Programming (OOP): Using classes and objects.
  • Classes and Objects: Blueprints and instances of data.
  • Encapsulation: Properties and methods.
  • Inheritance: Sharing behaviors between classes.
  • Design Patterns: Common ways to structure code.
  • Memory: Call stack for short-term, heap for long-term storage.

Concurrency and Parallelism

• Threads: Virtual cores on physical CPU cores.
• Parallelism: Code executing on different threads simultaneously.
• Concurrency: Handling multiple tasks on a single thread (event loop, co-routines).

Cloud Computing and Networking

• Virtual Machines: Software simulating hardware, fundamental to the cloud.
• Internet Protocol (IP): Identifies machines on a network via unique addresses.
• Domain Name Service (DNS): Maps URLs to IP addresses.
• TCP Handshake: Establishes connection to exchange messages.
• SSL/TLS: Encrypts messages for secure communication.
• HTTP/HTTPS: Protocols for client-server data exchange.
• API: Standardized data interaction, commonly REST architecture.

Conclusion

• Miscellaneous Knowledge: Understanding devices like printers, popular demand in tech help.