Mock Interviews

Feature Engineering Fundamentals

Learn to create powerful features from raw data. Encoding techniques, feature scaling, feature selection, and automated feature engineering approaches.

Building Chatbot Applications

Code conversational AI systems. Message handling, context management, streaming responses, and chatbot state management.

Design Ride-Hailing Platform

Matching, dispatch, surge pricing, maps & real-time updates.

Multi-threading & Concurrency

Concurrency-focused interview round: thread safety, deadlocks, race conditions, synchronization primitives, and concurrent data structures. Common in C++/Java backend roles.

Backend Engineer - Node.js

API design with Express/Fastify, authentication, SQL/NoSQL modeling, caching and observability.

Explaining ML Models to Stakeholders

Communicate ML concepts to non-technical audiences. Model interpretability discussions, setting realistic expectations, and translating technical metrics.

Supervised Learning Essentials

Deep dive into classification and regression. Covers linear regression, logistic regression, decision trees, and ensemble methods with practical examples.

Implementing ML Algorithms from Scratch

Code core ML algorithms without libraries. Linear regression, logistic regression, K-means, and gradient descent implementations.

Design News Feed

Fan-out, ranking, timelines, caching & cold-start strategies.