Computer Science Fundamentals
Big-O Notation for Self-Taught Programmers
- Big-O notation explained by a self-taught programmer
- Clear, practical explanation of algorithmic complexity
- Written from the perspective of a self-taught developer
- Bridges the gap between academic theory and practical programming
Understanding Big-O
- Time Complexity: How algorithm performance scales with input size
- Space Complexity: Memory usage scaling characteristics
- Common Complexities: O(1), O(log n), O(n), O(n log n), O(n²)
- Practical Impact: Real-world implications for application performance
Big-O Examples
- O(1): Hash table lookups, array access by index
- O(log n): Binary search, balanced tree operations
- O(n): Linear search, single loop through array
- O(n log n): Efficient sorting algorithms (merge sort, quicksort)
- O(n²): Nested loops, bubble sort, simple algorithms
Productivity and Neurodiversity
ADHD Productivity Tips from Reddit Community
- 131 ADHD pro-tips from 700+ Reddit comments
- Comprehensive collection of community-sourced productivity strategies
- Real-world tips from people with ADHD experience
- Covers work, organization, focus, and daily life management
Key ADHD Productivity Strategies
Focus and Attention
- Time Boxing: Work in short, defined time periods
- Pomodoro Technique: 25-minute focused work sessions
- Environmental Control: Minimize distractions and interruptions
- Task Switching: Use natural energy fluctuations
Organization Systems
- External Memory: Write everything down, don’t rely on memory
- Visual Reminders: Use calendars, sticky notes, and visual cues
- Routine Building: Create consistent daily and weekly routines
- Automation: Automate repetitive tasks and decisions
Work Strategies
- Hyperfocus Utilization: Leverage periods of intense focus
- Energy Management: Match tasks to energy levels throughout the day
- Accountability Systems: External accountability partners or systems
- Break Tasks Down: Large projects into smaller, manageable pieces
Learning and Development
Self-Taught Programming Challenges
- Knowledge Gaps: Filling in computer science fundamentals
- Learning Path: Structured approach to skill development
- Practical vs Theoretical: Balancing hands-on coding with theory
- Community Resources: Leveraging community knowledge and experience
Neurodiversity in Tech
- Different Thinking Styles: ADHD can bring creative problem-solving approaches
- Accommodation Strategies: Adapting work environments for different needs
- Strengths Recognition: Hyperfocus, creativity, and innovative thinking
- Support Systems: Community support and shared experiences
Key Takeaways
- Algorithmic Thinking: Understanding Big-O helps make better architectural decisions
- Community Wisdom: Real-world experience from communities provides valuable insights
- Neurodiversity: Different brains need different strategies for productivity
- Practical Learning: Self-taught programmers benefit from practical explanations of theory
- Adaptive Strategies: What works for neurotypical individuals may not work for everyone
These resources highlight both technical learning (algorithm analysis) and personal productivity strategies, showing how understanding both code complexity and personal working styles contributes to developer effectiveness.