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AP CSP Tri 1


Sprint 2 Final Project and Culmination of Lessons

Variables (3.1)
> Store data values that can be changed
> Container to hold and manipulate information
Data Abstraction (3.2)
> Simplify complex data structures
> Make programs easy to understand
> Ensure correct use cases
Mathematical Expressions (3.3)
> Operations involving numerical values
Strings (3.4)
> Text values enclosed in quotes
> Text can be utilized
Boolean Expressions (3.5)
> Logical statements
> Simplify down to true or false
> Basis of conditionals and decision making
Conditionals (3.6)
> Allow program to complete action based on input
> Reduce user input
> Increase autonomy
Nested Conditionals (3.7)
> Conditionals in conditionals
> Add complexity in decision-making process
> Edge-case simplification
Iteration (3.8)
> Repeat code multiple times
> Perform repetitive tasks effectively
> Simplify code
List Operations (3.10)
> Modifying list elements
> Manage collections of data
Javascript Self Study (3.15)
> Display sprite through sprite sheet
> Interact with DOM through JS




AP CSP Tri 3

Beneficial & Harmful Effects (5.1)
> Computing innovations impact society
> Effects can be both beneficial and harmful
> Unintended consequences can occur
Digital Divide (5.2)
> Unequal access to technology
> Socioeconomic, geographic & demographic factors
> Impact on education and opportunities
Computing Bias (5.3)
> Bias in algorithm development
> Influence on data interpretation
> Social implications of biased systems
Crowdsourcing (5.4)
> Leveraging collective intelligence
> Distributed problem-solving
> Collaborative data collection
Legal & Ethical Concerns (5.5)
> Intellectual property rights
> Privacy in digital environments
> Ethical use of technology
Binary Search (3.11)
> Efficient searching algorithm
> Requires sorted data
> Divide and conquer approach
Safe Computing (5.6)
> Cybersecurity principles
> Protecting personal data
> Threat mitigation strategies
Lists & Filtering (3.10)
> Data structure manipulation
> Filter operations on collections
> Processing data efficiently
Algorithmic Efficiency (3.17)
> Big O notation analysis
> Time and space complexity
> Algorithm performance evaluation
Randomness & Simulations (3.15)
> Random number generation
> Game theory applications
> Modeling probabilistic scenarios

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Sprint 1: Initial Startup

Starting off with tools setup and understanding jupyter

Week Plans Hacks Tangibles
1 No tangibles
2 No plans No tangibles
3 No plans No hacks
4 No plans No hacks

Sprint 2: Team Teach

Creating and participating in lessons

Week Plans Hacks Tangibles
5 No hacks No tangibles
6 No plans No tangibles
7 No plans No hacks No tangibles
8 No plans No tangibles
9 No plans No hacks No tangibles

Trimester 1 Final: Beginning Flocker

Presented at Night at the Museum

Week Plans Hacks Tangibles
10 No plans No hacks No tangibles
11 No plans No hacks No tangibles
12 No plans No hacks No tangibles

Sprint 3: New Teams

Starting off Tri2 strong

Week Plans Hacks Tangibles
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14 No tangibles
15 No plans No hacks No tangibles
16 No plans No hacks No tangibles

Sprint 4: Understanding the Backend//Flask

Prism - The first project

Week Plans Hacks Tangibles
14 No tangibles
15 No plans No hacks No tangibles
16 No plans No hacks No tangibles
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18 No plans No hacks

Sprint 5: Moving into Dynamic Connectivity

Prism

Week Plans Hacks Tangibles
19 No plans No hacks No tangibles
20 No plans No hacks No tangibles
21 No plans No hacks No tangibles
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23 No tangibles

Sprint 7: Starting Trimester 3 Off

Machine Learning

Week Plans Hacks Tangibles
24 No plans No tangibles
25 No plans No hacks No tangibles
26 No plans No hacks No tangibles
27 No plans No hacks No tangibles
28 No plans No tangibles

Team Teach: Starting Trimester 3 Off

Machine Learning

Week Plans Hacks Tangibles
28 No plans No tangibles
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32 No plans No hacks No tangibles