AI & Machine Learning
Machine learning, deep learning, LLMs, model evaluation and production AI systems.
Why RAG Systems Fail: Build, Debug, and Evaluate Retrieval in PythonBuilding a Reliable AI Agent in Python: Tool Calling, State, Retries and RecoverySemantic Search in Python: BM25 vs Embeddings vs Hybrid RetrievalData Leakage in Machine Learning: Five Python Experiments That Fool Model EvaluationHow to Evaluate LLM Applications in Python: Build a Reproducible Testing HarnessAI Skill AssessmentWhat Should an AI Engineer Know in 2027?Common Machine Learning Knowledge GapsRAG vs Fine-Tuning vs Prompting
Java & Backend
Core Java, Spring Boot, persistence, concurrency and backend system design.
Java Virtual Threads vs Platform Threads: A Reproducible Spring Boot BenchmarkHow Spring Boot Transactions Fail Under Concurrency: Prevent Overselling with Java and SQLJava Skill AssessmentWhat Should a Senior Java Developer Actually Know?How to Prepare for a Java Technical InterviewJava Concurrency Interview Topics for Senior Developers
Quantitative Finance
Probability, statistics, stochastic models, derivatives pricing, risk and financial markets.
Interest Rate Swap Pricing in Python: Yield Curves, Discount Factors and DV01Kalman Filter for Crypto Pairs Trading: Dynamic Hedge Ratios in PythonMonte Carlo Option Pricing in Python: Black–Scholes, Confidence Intervals, and Variance ReductionQuantitative Finance Skill AssessmentHow to Prepare for a Quantitative Finance InterviewBlack-Scholes Model: What Should You Actually Understand?Monte Carlo Methods in Quantitative FinanceCommon Quant Finance Knowledge GapsMean Reversion Trading in Python: BTC–ETH Pairs Trading, Z-Scores, Cointegration, and Backtesting
Blockchain & Smart Contracts
Blockchain architecture, smart contracts, Web3, DeFi, protocol design and security.