Homework Certification

A collection of the homework lessons I completed over the year.

• 3 min read

Homework Submission Table

Homework Title Link
3.1 View
3.2 View
3.3 View
3.4 View
3.5 View
3.6 View
3.7 View
Digital Divide View
Lists and Filtering View
Simulation/Games View
BigO View
Binary View
Base 64 View

CSP Lesson Notes

1. Beneficial & Harmful Effects of Computing

Beneficial Examples

  • Automated telephone trees (saves time and money)
  • Medical technology: MRI, DNA sequencing
  • Access to education: online resources, search engines

Harmful Examples

  • Cyberbullying and scams
  • Social media’s mental health effects
  • Ethical dilemmas in autonomous systems

Neutral / Debatable

  • AI: productivity vs. misuse (e.g., deepfakes, cheating)
  • Drones: agriculture vs. privacy
  • Gene editing: cures vs. ethical risks

2. The Digital Divide

  • Causes: Economic, geographic, and societal factors
  • Impacts: Education gaps, employment inequality, limited telemedicine, reduced civic engagement
  • Solutions:
    • Infrastructure improvements
    • Subsidized access
    • Inclusive technology
    • Equity-focused policy

3. Computing Bias

Definition: Unfair algorithmic outcomes due to flawed logic or data

Sources:

  • Data bias
  • Algorithmic bias
  • Human (cognitive) bias

Types:

  • Explicit vs. implicit data
  • Intentional vs. unintentional bias

Mitigation Strategies:

  • Pre-processing: Clean training data
  • In-processing: Adjust learning process
  • Post-processing: Monitor and audit outputs

4. Crowdsourcing & Distributed Computing

Types of Crowdsourcing:

  • Crowdfunding
  • Crowd creation (e.g., Wikipedia)
  • Crowd voting
  • Crowd wisdom

Examples:

  • Waze
  • Kickstarter
  • Mechanical Turk
  • SETI@home

Challenges:

  • Quality control
  • Coordination
  • Privacy concerns

5. Legal & Ethical Concerns in CS

Licenses:

License Permissions Restrictions Best Use
MIT Free use, modify, distribute No liability Small projects, web tools
Apache 2.0 MIT + patent protection Must include license Corporate APIs
GPL Must stay open-source No proprietary forks Nonprofits, open software
BSD 3-Clause Use freely, no misrepresentation No warranty Academic or closed-source projects
Creative Commons For non-code (e.g., docs, images) Some attribution required Documentation, media

Ethical Issues:

  • Proper attribution
  • Abuse of open-source contributions
  • Licensing compliance

6. Safe Computing

  • PII: Personally Identifiable Information
  • Cookies: Session vs. persistent
  • Passwords: Use strong, unique combinations
  • Encryption Types:
    • AES (symmetric)
    • RSA (asymmetric)
    • SHA-256 (hashing)
  • Phishing: Spoofed emails and fake websites
  • Verification Tools:
    • MFA (Multi-Factor Authentication)
    • CAPTCHAs
    • Digital signatures

7. Binary Search Algorithm

Comparison to Linear Search:

  • Binary search: Requires sorted input, O(log n)
  • Linear search: No sort needed, O(n)

Steps:

  1. Compare target to the middle value
  2. Recurse left or right based on comparison
  3. Stop when found or when bounds cross

Applications: Dictionaries, search engines, databases

8. Lists & Filtering Algorithms

  • Lists: Mutable, ordered collections
  • Common Operations: append, remove, slice, sort
  • Filtering: Conditional logic using loops
  • Use Cases: Email filters, search suggestions

9. Random Number Generation

  • Purpose: Games, cryptography, simulations
  • Function: random(a, b) → returns a random integer from a to b
  • Use Cases: Monte Carlo methods, randomized testing

10. Big O & Algorithmic Efficiency

Why It Matters:

  • Faster user experience
  • Better scalability
  • Reduced resource usage

Common Big O Classes:

  • O(1): Constant time (e.g., array lookup)
  • O(log n): Binary search
  • O(n): Simple loops
  • O(n log n): Merge sort
  • O(n²): Bubble sort

Reflection

Throughout the year, I developed both technical skills and a deeper understanding of the broader implications of computing. I learned how algorithmic decisions can reflect real-world biases, explored the ethics of open-source licensing, and practiced writing efficient and secure code. These lessons were not just theoretical; I applied them through hands-on projects and classroom discussions. By the end of the course, I gained the confidence to engage with computing critically and responsibly, not just as a programmer, but as a thoughtful contributor to the digital world.