Name: 🌶️ AP Comp Sci P Cram Review: Big Idea 2: Data
Uploaded: 2021-03-16T22:00:00.000Z
Description: Big Idea 2: Data

AP Computer Science Principles

Unit 1 – Creative Development

1.1 Collaboration

Unit 2 – Data in AP Computer Science Principles

2.2 Data Compression

Unit 3 – Algorithms & Programming Fundamentals

3.3 Mathematical Expressions

Unit 4 – Computer Systems & Networks

4.1 The Internet

Unit 5 – Computing's Impact on Society

Big Idea 5 Overview: Impact of Computing

Frequently Asked Questions

How Can I Be Prepared for the AP Computer Science Performance Task?

Previous Exam Prep

Big Idea 1: Creative Development 

AP Cram Sessions 2021

🌶️ AP Comp Sci P Cram Review: Big Idea 3: Algorithms and Programming

First Unit

Study Tools

2024 AP Computer Science Principles Exam Guide

Exam Skills

Score Higher on AP Comp Sci P 2024: MCQ Tips from Students

Developing an Understanding

Summary of Upcoming Topics:

Big Idea 1 Overview: Creative Development

Computing Innovations

Collaboration in Computer Science

Collaboration Between Users and Developers

Computing Developments that Foster Collaboration

Ways to be a Good Team Player!

Collaboration

Computing Innovations and Their Purposes

Programs and Code Segments... with Cake

Describing Programs

Program Inputs

Program Outputs

Program Events

Program Behavior

Program Function and Purpose

Types of Development Processes

Iterative and Incremental Development Processes

The Drawing Board: Phases of Program Development

Program Requirements and Specifications

Program Documentation

Sourcing Your Work

Program Design and Development

Common Errors

Error Fixes

Testing 

Error-Hunting Example

Whew!

Identifying and Correcting Errors

Number Bases

Bit Representations

Abstraction

The One Thing You Need to Know About this Big Idea:

2.1 Binary Numbers

2.3 Extracting Information from Data

2.4 Using Programs with Data

Exam Weighing

Big Idea 2 Overview: Data

Data Compression Examples

Lossless vs. Lossy Data Compression

Data Compression

Metadata

Problems Collecting and Processing Data

Data Biases

Extracting Information from Data

Transforming Data

Data Analysis Discoveries

In conclusion...

Using Programs with Data

Unit 2 – Data

The One Thing You Need to Know About This Big Idea:

3.1 Variables and Assignments

3.2 Data Abstraction

3.4 Strings

3.5 Boolean Expressions

3.6 Conditionals

3.7 Nested Conditionals

3.8 Iteration 

3.9 Developing Algorithms

3.10 Lists

3.11 Binary Search

3.12 Calling Procedures

3.13 Developing Procedures

3.14 Libraries

3.15 Random Values

3.16 Simulations

3.17 Algorithmic Efficiency

3.18 Undecidable Problems

Exam Weighing:

Big Idea 3: Algorithms and Programming

Variables in Pseudocode and Python

Data Types

Variables and Assignments

Basic List Operators

Adding and Removing Elements

Looping through Lists

Lists

Traversing a List

Binary Search

Parts of a Procedure:

Calling Procedures

Procedural Abstraction

Developing Procedures

API Software Libraries

Libraries

Generating Random Numbers

Random Values

Abstraction in Simulations

Simulations

Problems

Efficiency

Algorithmic Efficiency

Conclusion

Undecidable Problems

Lists in AP CSP Pseudocode

Data Abstraction

Sequencing

Expressions

Mathematical Expressions

What are Strings?

Strings

Boolean Variables

Not, And, Or

Boolean Expressions

If Statement

Else Statement

Conditionals

Nested Conditional Example

Nested Conditionals

Repeat n Times

Repeat Until (condition)

Iteration Practice Problem

More Operators in Loops

Iteration

Existing Algorithm Types

Developing Algorithms

Unit 3 – Algorithms & Programming

4.2 Fault Tolerance 

4.3 Parallel and Distributed Computing

Example Problem 

Big Idea 4 Overview: Computer Systems and Networks

Computing Devices, Systems, and Networks

Data Streams, Packets, and Routing

Bandwidth

Internet Protocols

The World Wide Web

Scalability

The Internet

What is Fault Tolerance?

Redundancy

Benefits of Fault Tolerance

Disadvantages of Fault Tolerance

Fault Tolerance

Parallel and Distributed Computing Definitions

Execution Time, Efficiency, and Speedup Calculations

Calculating Execution Time 

Calculating the Speedup

Speed Limits

Example Problem

In Conclusion...

Parallel and Distributed Computing

5.1 Beneficial and Harmful Effects

5.2 Digital Divide

5.3 Computing Bias

5.4 Crowdsourcing

5.5 Legal and Ethical Concerns

5.6 Safe Computing

Big Idea 5 Practice Problems and Solutions

Beneficial Effects of Computing Innovations

Harmful Effects of Computing Innovations

Unintended Effects of Computing Innovations

Beneficial and Harmful Effects

Factors that Influence the Digital Divide

Harmful Impacts of the Digital Divide

Reducing the Digital Divide

Digital Divide

What is Bias?

Examples of Bias

What can we do to prevent bias in computing?

Computing Bias

Citizen Science

Examples of Citizen Science

Crowdsourcing

Examples of Crowdsourcing 

Intellectual Property

Copyright

Plagiarism

Legal Ways to Use The IP of Others

Other Legal and Ethical Concerns

In Summary…

Legal and Ethical Concerns

Information Collection

Benefits and Harms of Information Collection

Other Dangers of Computing

Principles of Safe Computing

Other Safe Computing Practices

Safe Computing

Unit 5 – Impact of Computing

🌶️ AP Comp Sci P Cram Review: Big Idea 2: Data

🌶️ AP Comp Sci P Cram Review: Big Idea 2: Data

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