Algorithms and Programming

Congratulations for making it this far!

What you will learn

This is part two of College Board’s Big Idea 3.

Part 1 - Fundamentals (Previous unit)

In the previous unit, you covered the foundational concepts of programming, including:

  • 3.1 Variables
  • 3.2 Data Abstraction
  • 3.3 Mathematical Expressions
  • 3.4 Strings
  • 3.5 Booleans
  • 3.6 Conditionals
  • 3.7 Nested Conditionals
  • 3.8 Iteration
  • 3.10 Lists

Part 2 - Core Concepts (This unit)

In this unit, you will delve into more complex topics, such as:

  • 3.9 Developing Algorithms
  • 3.11 Search
  • 3.12 Calling Procedures
  • 3.13 Developing Procedures and Procedural Abstraction
  • 3.14 Libraries
  • 3.15 Random Values
  • 3.16 Simulations
  • 3.17 Algorithmic Efficiency
  • 3.18 Undecidable Problems

Why it matters

These concepts will help you grow in coding style and proficiency. Mastering these topics will prepare you for coding in a system, rather than the simplicity of coding in a single code cell. This knowledge is crucial for developing more sophisticated and efficient programs, and it will be invaluable as you progress in your computer science journey.

Continuing on next Topics

In this unit, the topics are more complex and combine theory and programming. Provided are a few terms, but don’t worry if you don’t understand them at first as it is the purpose of the lesson to help you grow in the concepts.

Basic Terms

  • Efficiency: A measure of how well an algorithm performs, particularly in terms of time and space resources.
  • Procedures: A programming language structure that encapsulates a sequence of statements to perform a specific task. Often called a method, function, or subroutine.
  • Libraries: Collections of pre-written code that you can import into your programs to add functionality without having to write the code from scratch.
  • Random Values: Values generated by a process that cannot be predicted beforehand. Coding languages contain functions to create random numbers, which are useful in simulations and games.
  • Simulations: Algorithms designed to model the behavior of real-world systems or processes over time.
  • Undecidable Problems: Problems for which no algorithm can be constructed that always leads to a correct yes-or-no answer.

Resource

For more detailed information and resources, visit the official College Board AP CSP page.