• Python, TensorFlow, NumPy, Pandas

• Focus: Machine Learning, AI, Neural Networks
• Built neural network models for prediction tasks
• Applied backpropagation and gradient descent optimization
• Designed and evaluated model performance pipelines
• Visualized results and analyzed metrics

    • Python, Scikit-learn, Pandas

• Focus: Data Analysis, Machine Learning, Predictive Modeling
• Built end-to-end financial prediction pipeline
• Applied feature engineering and statistical learning
• Performed trend analysis and forecasting
• Improved model accuracy via tuning

    • SQL (PostgreSQL)

• Designed normalized relational database schema
• Optimized SQL queries for performance (~30% improvement)
• Built KPI tracking and reporting workflows

    • Java, Clojure

• Designed modular backend service architecture
• Implemented API-driven system integration layer
• Applied systems and communication patterns
• Developed RESTful APIs and backend services

• Data Structures and Algorithms (Python, Java, C++) with complexity optimization
• System Design (scalable, distributed, fault-tolerant architectures)
• Object-Oriented Programming + Functional Programming (Clojure / ClojureScript)
• Concurrency, parallelism, and performance optimization
• Design of high-performance and maintainable software systems

• Neural Networks (TensorFlow, Scikit-learn) for predictive systems
• Machine learning pipelines and end-to-end ML workflows
• Predictive modeling, feature engineering, and statistical learning
• Data analysis, visualization, and exploration (Pandas, NumPy, Matplotlib)
• Applied ML systems for real-world data-driven decision making

• Production-grade backend systems (Java, Python, Clojure)
• REST API design, microservices, and system architecture
• Distributed systems fundamentals (scalability, reliability, availability)
• Service-oriented architecture and system integration
• Building robust and scalable backend services

• SQL (PostgreSQL) – complex queries and optimization
• Data modeling for scalable and efficient systems
• Query optimization and performance tuning
• Relational database design and data integrity

• Data Structures and Algorithms • System Design • Distributed Systems
• Machine Learning Engineering • Data Engineering • Scalable Backend Systems
• Production-grade Architecture • High-performance Software Design