DSA & System Design 1:1 Mentorship

Karan Kumar

profile
DSA & System Design 1:1 Mentorship
profile
FREE
30 mins

I’m Karan, a Backend Engineer & Mentor with 4+ years of experience in Java, Microservices, and scalable system architecture. I’ve helped students and professionals land offers at top companies by simplifying interview prep.

💡 What You’ll Learn in 1:1 Mentorship

🔷 Data Structures & Algorithms (DSA)

  • Arrays, Strings, LinkedList, Stack, Queue, Trees, Tries
  • Graphs, Topological Sort, Union-Find
  • Recursion, Backtracking
  • Dynamic Programming
  • Sliding Window, Two Pointers, Binary Search
💬 With line-by-line dry-run explanations — like how you’d explain in an interview.

🔷 LeetCode Patterns Mastery

  • Understand common patterns: Merge Intervals, Greedy, Monotonic Stack, BFS/DFS
  • Build problem-solving intuition
  • Focus on FAANG/Top Product company questions
🧩 Not just how to solve, but why it works.

🔷 Mock Interviews + Feedback

  • Real-time interview simulation
  • Feedback on your thought process, approach, and communication
  • Live debugging + behavioral guidance
💡 Includes feedback on how to think like an interviewer.

🔷 Advanced System Design (LLD + HLD)

Learn how to design, scale, and reason like a staff engineer.

✅ Low-Level Design (LLD)
  • Object-Oriented Design
  • SOLID, DRY, Encapsulation & Composition
  • Live Coding:
    • Parking Lot
    • Ludo
    • Chess
    • Wallet System
    • To-Do List App
    • Rate Limiter
🎓 We’ll go class-by-class with UML + code
✅ High-Level Design (HLD)
Master the “why” before the “what” — understand trade-offs, components, and real-world scale.
  • API Gateway + Microservices
  • Load Balancing + Consistent Hashing
  • Database Sharding, Replication, Partitioning
  • Caching (Redis, Memcached)
  • Messaging Queues (Kafka, RabbitMQ)
  • Search Engines (Elasticsearch)
  • Distributed Systems: CAP Theorem, Eventual Consistency
  • Design Dropbox, Instagram, YouTube, WhatsApp, Rate Limiter, Netflix
🛠 We'll whiteboard it out, design end-to-end flows, and dive into:
  • Read/Write optimizations
  • Scaling storage + compute
  • Designing for failure