Structure & Rules

Program Structure

• 40% Theory

  • Follow structured AI/ML roadmap
  • Understand concepts deeply before coding
  • Focus on intuition + math foundation

• 40% Implementation

  • Implement algorithms from scratch
  • Then implement using libraries (NumPy, pandas, scikit-learn, etc.)
  • Compare manual vs library performance

• 20% Project Work (Mizban)

  • Start thinking about real-world system design
  • Identify possible AI use-cases in Mizban
  • Discuss architecture ideas
  • First month → research + ideation phase

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Daily Requirements

Every day, each intern must:

• Push code to GitHub
• Write what you learned (short daily summary)
• Ask at least 3 technical questions
• Solve 5–10 problems (coding/math/logic)

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Engineering Discipline

• Use proper commit messages
• Follow a clean folder structure
• Write readable code (naming matters)
• No copy-paste without understanding

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Documentation Habit

• Maintain:

  • README.md updates
  • Personal learning notes
  • Algorithm explanation in comments