AP® Computer Science Principles Cheat Sheet

A comprehensive resource for AP Computer Science Principles. This expertly crafted cheat sheet provides a concise overview of essential topics, including algorithms, data management, and computer systems, ensuring you are fully prepared for your exams.

Download AP Computer Science Principles Cheat Sheet – Pdf

Unit 1: Creative Development

• Computing Tools: software, hardware, IDEs, etc.
• Program Design: flowcharts, pseudocode, testing strategies
• Collaboration: roles, pair programming, code review, version control
• Algorithms: step-by-step procedures, sequencing, selection, iteration
• Problem-Solving Process: define, plan, implement, test, reflect
• Abstraction: simplifying complex problems by focusing on the main ideas
• Digital Representation: binary, data compression, and data storage

Unit 2: Data

• Data Types: numbers, strings, booleans, lists, etc.
• Data Representation: binary, hexadecimal, text (ASCII/Unicode)
• Data Collection: surveys, sensors, databases, web scraping
• Data Storage: cloud, local storage, databases
• Data Analysis: filtering, sorting, visualizing with graphs/charts
• Big Data: large datasets, machine learning, predictive analysis
• Data Security: encryption, privacy laws (GDPR, HIPAA)

Unit 3: Algorithms & Programming

• Programming Languages: high-level vs. low-level, syntax, semantics
• Variables: declaration, initialization, assignment, scope
• Control Structures: if-else, loops (for, while), switch-case
• Functions: definition, parameters, return values, recursion
• Debugging: syntax errors, runtime errors, logic errors, testing
• Program Efficiency: time complexity, space complexity (Big-O notation)
• APIs: libraries, functions, documentation, integration

Unit 4: Computer Systems & Networks

• Computer Components: CPU, memory, storage, input/output devices
• Operating Systems: tasks, file management, user interface
• Internet: IP, DNS, HTTP, protocols, packet-switching
• Network Types: LAN, WAN, VPN, peer-to-peer, client-server
• Cybersecurity: firewalls, antivirus, encryption, phishing, malware
• Data Transmission: bandwidth, latency, throughput
• Cloud Computing: SaaS, IaaS, PaaS, distributed computing

Unit 5: Impact of Computing

• Ethics: privacy, digital divide, intellectual property, hacking
• Legal Issues: copyright, patents, fair use, DMCA
• Social Impacts: social media, AI ethics, job automation, bias
• Global Impact: digital communication, internet access, globalization
• Economic Impact: e-commerce, fintech, gig economy
• Environmental Impact: e-waste, energy consumption, green computing
• Future Trends: AI, quantum computing, blockchain, IoT

Unit 6: Simulation & Modeling

• Simulations: virtual models, predictions, testing hypotheses
• Modeling: abstract representations, simplifications of reality
• Randomness: random number generation, Monte Carlo methods
• Heuristics: problem-solving approaches, approximation algorithms
• Data Visualization: graphs, charts, dashboards, infographics
• System Modeling: input-output models, flowcharts, state diagrams
• Decision Making: cost-benefit analysis, risk assessment, optimization