📊 Module 03: Algorithms¶

Estimated Time: 15-20 hours
Prerequisites: Modules 01 (Foundations), 02 (Data Structures)
Level: ⭐⭐⭐ Intermediate

🎯 What You'll Learn¶

Algorithms are step-by-step procedures for solving problems. In this module, you'll master:

Searching — Finding elements efficiently
Sorting — Organizing data in order
Recursion — Solving problems by breaking them into smaller pieces
Dynamic Programming — Optimizing by storing subproblem solutions
Greedy Algorithms — Making locally optimal choices
Divide and Conquer — Breaking problems into independent subproblems
Graph Algorithms — Traversing and analyzing connected data

📚 Topics¶

#	Topic	Description	Key Concepts
01	Searching	Finding elements in collections	Linear search, binary search
02	Sorting	Ordering elements	Bubble, selection, insertion, merge, quick sort
03	Recursion	Self-referential problem solving	Base case, recursive case, call stack
04	Dynamic Programming	Optimization through memoization	Overlapping subproblems, optimal substructure
05	Greedy Algorithms	Local optimization strategies	Greedy choice property, activity selection
06	Divide and Conquer	Breaking down problems	Merge sort, quick sort, binary search
07	Graph Algorithms	Traversing connected structures	BFS, DFS, shortest paths

🧠 Why Algorithms Matter¶

"An algorithm must be seen to be believed." — Donald Knuth

Understanding algorithms helps you:

Write efficient code — Choose the right approach for each problem
Pass technical interviews — Algorithms are a core interview topic
Think systematically — Break complex problems into manageable steps
Optimize performance — Know when O(n) vs O(n²) matters

📖 How to Study This Module¶

Step 1: Understand the Concept¶

Read each topic's README to understand: - What problem the algorithm solves - How it works (step by step) - When to use it - Time and space complexity

Step 2: Study the Examples¶

Run and modify examples.py to see algorithms in action:

cd 03_algorithms/01_searching
python examples.py

Step 3: Practice¶

Complete the exercises in exercises.py: - Start with the easier problems - Write code before looking at hints - Test with different inputs

Step 4: Test Your Knowledge¶

Take the quiz in quiz.md to verify understanding.

🔑 Key Complexity Classes¶

Understanding Big-O notation is crucial for this module:

Notation	Name	Example
O(1)	Constant	Array access by index
O(log n)	Logarithmic	Binary search
O(n)	Linear	Linear search
O(n log n)	Linearithmic	Merge sort
O(n²)	Quadratic	Bubble sort
O(2ⁿ)	Exponential	Naive recursive fibonacci

🗺️ Learning Path¶

01_searching ──────┐
                   ├──► 03_recursion ──► 04_dynamic_programming
02_sorting ────────┤                          │
                   │                          ▼
                   └──► 06_divide_and_conquer

02_sorting ──────────► 07_graph_algorithms (uses DFS/BFS)

Recommended order: 1. Start with Searching — simplest algorithms 2. Move to Sorting — builds on comparisons 3. Learn Recursion — fundamental technique 4. Study Divide and Conquer — applies recursion 5. Tackle Dynamic Programming — optimizes recursion 6. Explore Greedy Algorithms — alternative approach 7. Finish with Graph Algorithms — combines everything

💡 Tips for Success¶

Trace through by hand — Draw arrays and step through algorithms on paper
Visualize — Use sites like visualgo.net to see algorithms animate
Implement from scratch — Don't just read, write the code yourself
Analyze complexity — Always think about time and space
Practice variations — Same algorithm, different problems

📂 Module Structure¶

03_algorithms/
├── README.md (this file)
├── 01_searching/
│   ├── README.md
│   ├── examples.py
│   ├── exercises.py
│   └── quiz.md
├── 02_sorting/
│   ├── README.md
│   ├── examples.py
│   ├── exercises.py
│   └── quiz.md
├── 03_recursion/
│   ├── README.md
│   ├── examples.py
│   ├── exercises.py
│   └── quiz.md
├── 04_dynamic_programming/
│   ├── README.md
│   ├── examples.py
│   ├── exercises.py
│   └── quiz.md
├── 05_greedy_algorithms/
│   ├── README.md
│   ├── examples.py
│   ├── exercises.py
│   └── quiz.md
├── 06_divide_and_conquer/
│   ├── README.md
│   ├── examples.py
│   ├── exercises.py
│   └── quiz.md
└── 07_graph_algorithms/
    ├── README.md
    ├── examples.py
    ├── exercises.py
    └── quiz.md

✅ Completion Checklist¶

Complete all 7 topic READMEs
Run and understand all examples
Solve at least 3 exercises per topic
Pass all quizzes with 80%+ score
Implement one algorithm from memory

Ready to start? Begin with 01_searching!