Study Guides with links

Study Plan

1. Review Team Teach pages, create notes for them and a plan for review to put into flashcards (notes are below will organize better)
2. Review Collegeboard Videos and practice key topics with flashcards
3. AP Computer Science Principles Student Handout <- Review the student Handbook

AP CSP Review Materials

• Computing Innovations
• Digital Divide
• Crowdsourcing in Computing
• Legal and Ethical Team Teach
• Python Lists and Filtering Algorithms
• Random Algorithms & Simulations
• Graphs & Heuristics
• Logic Gates
• Images & Encoding Study
• Sprint 5 Blog & Review

📘 AP Computer Science Principles (AP CSP) Overview

🧠 Big Ideas

1. Creative Development (CRD)

• Emphasizes collaboration in program development.
• Utilizes iterative processes: investigating, designing, prototyping, and testing.
• Focuses on program design and development.
• Exam Weight: 10%–13%

2. Data (DAT)

• Explores how computers handle and process data.
• Covers data compression and extracting information from data.
• Exam Weight: 17%–22%

3. Algorithms and Programming (AAP)

• Involves developing algorithms and using abstractions.
• Includes simulations and algorithmic efficiency.
• Exam Weight: 30%–35%

4. Computer Systems and Networks (CSN)

• Studies how computer systems and networks operate.
• Topics include the Internet and parallel/distributed computing.
• Exam Weight: 11%–15%

5. Impact of Computing (IOC)

• Examines the effects of computing on society, economy, and culture.
• Discusses the digital divide, computing bias, and safe computing practices.
• Exam Weight: 21%–26%

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4.1-4.3: The Internet & Computing Models

4.1: The Internet Fundamentals

• Computing Devices & Systems: A computing device is a physical artifact that can run a program (computers, tablets, servers, routers)
• Computer Networks: Interconnected computing devices capable of sending/receiving data
• Routing: Finding a path from sender to receiver through a sequence of connected devices
• Bandwidth: Maximum data sent in fixed time (measured in bits per second)
• Internet Protocols: Standardized, open (nonproprietary) communication rules
• Scalability: The Internet was designed to change in size and scale to meet new demands

4.2: Fault Tolerance

• Fault Tolerance: Enables a system to continue functioning despite failures in components
• Redundancy: Including extra components to mitigate failure
• Network Redundancy: Having multiple paths between connected devices
• Routing Adaptability: If a path fails, data can be sent via different routes
• Benefits: Continued operation during unexpected failures, ability to scale to more devices/users
• Challenges: Requires additional resources to implement redundancy

4.3: Computing Models & Efficiency

• Sequential Computing: Operations performed one at a time in order
• Parallel Computing:
  • Program broken into smaller operations performed simultaneously
  • Contains both parallel and sequential portions
  • More scalable than sequential computing
  • Limited by sequential portion (Amdahl's Law)
• Distributed Computing:
  • Uses multiple devices to run a program
  • Solves problems too large for single computers
  • Allows larger problems to be solved more quickly
• Efficiency Calculations:
  • Sequential: Total time = sum of all steps
  • Parallel: Total time = sequential tasks + longest parallel task
  • Speedup = (Sequential time) / (Parallel time)

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