Build a scalable ride-sharing app using SOLID principles, Strategy & Observer patterns, and real-world architectural tradeoffs.

Break down a real-world architecture using SOLID principles and clean abstractions.

Implement dynamic fare logic and real-time ride updates with proven design patterns.

Apply class-level design that supports scaling across new features and components.
Tackle architecture questions with structured thinking and real-world examples.
Data Engineer at Replit building observability tools and scalable infrastructure for ML systems.
Ex-AWS & LinkedIn, with hands-on experience in production-grade ML observability and real-time data engineering.
ML Infra Specialist, ML Infra Specialist, with a deep focus on explainability, reproducibility, and debugging in applied AI.
FAANG+ Interview Mentor, guiding professionals on breaking into top Data and ML roles.
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Get 50% of your tuition refunded if no job is secured.
Hear it from our Alumni.
Apply Strategy and Observer Patterns:
Implement modular pricing and real-time updates with clean design patterns.
Build for Scale with SOLID Foundations:
Structure systems that are extensible, testable, and interview-ready.
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Time Zone: Asia/Kolkata
Time Zone: Asia/Kolkata
Hands-on AI/ML learning + interview prep to help you win
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Design a ride-sharing platform using SOLID principles — and crack FAANG+ system design interviews.
Break down rider-driver flows, pricing logic, and trip lifecycle.
Learn how top engineers handle real-world constraints at scale.
Master interview strategies for designing feature-rich systems.
Design a ride-sharing platform using SOLID principles — and crack FAANG+ system design interviews.
Time Zone: Asia/Dhaka
Time Zone: Asia/Dhaka
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