(#CodeWithVarun: DSA & System Design in 60 Days)
🔹 1. What is DSA?
Data Structures and Algorithms (DSA) are the foundation of computer science and software engineering.
- Data Structures → Organized ways to store and manage data (arrays, stacks, queues, trees, graphs).
- Algorithms → Step-by-step procedures to solve problems efficiently (sorting, searching, pathfinding).
Together, they form the toolkit every engineer uses to solve problems in the real world.
🔹 2. Why Does DSA Matter?
- Efficiency Matters
- Two solutions can solve the same problem, but one might be 10x faster.
- Example: Searching a word in a dictionary → Linear search vs Binary search.
- Scalability
- Apps today serve millions of users. Without efficient DSA, systems slow down or crash.
- Example: Instagram showing feeds → optimized data structures make it smooth.
- Interviews
- Top companies test DSA because it reflects problem-solving skills, logic, and optimization mindset.
- It’s not about memorization, but about how you think through problems.
- Real-World Applications
- Maps (Graphs + Dijkstra’s Algorithm).
- Search Engines (Tries + Ranking Algorithms).
- Social Media Feeds (Heaps, Queues, HashMaps).
🔹 3. Categories of DSA
To make it easier, we’ll cover:
- Linear Data Structures → Arrays, Linked Lists, Stacks, Queues.
- Non-Linear Data Structures → Trees, Graphs, Hash Tables.
- Algorithms → Sorting, Searching, Greedy, Divide & Conquer, Dynamic Programming, Graph Algorithms.
🔹 4. How to Approach DSA Learning
✅ Focus on concepts first, then problems.
✅ Solve easy → medium → hard problems progressively.
✅ Practice patterns (sliding window, two pointers, divide & conquer).
✅ Most importantly → write and debug code yourself.
🔹 5. What’s Next?
Tomorrow, we start with the most basic yet powerful structure → Arrays.
- How they work.
- Why they matter.
- Real-world applications.
- Common interview problems.
👉 Follow the series daily on LinkedIn and the blog: #CodeWithVarun: DSA & System Design in 60 Days