─────── § ───────
─────── § ───────
| Data Engineering & MLOps | ||
|---|---|---|
| Architecture & Processing | Storage & Infrastructure | Operations & Delivery |
| Spark (Scala/Python), Kafka, Flink, Airflow/Dagster, Databricks, dbt, Glassflow | Lakehouse (Delta/Iceberg), Vector DBs (Qdrant, etc.), Cloud (AWS/Azure/GCP), IaC (NixOS, Terraform) | Docker, Kubernetes, Kubeflow, CI/CD for ML, GitOps, Observability, FastAPI |
| Machine Learning & AI | ||
|---|---|---|
| Modeling & Frameworks | Specializations | Methodology |
| Python (Pandas, NumPy, Scikit-learn, XGBoost), TensorFlow, PyTorch | NLP (Transformers), GenAI (LangChain, LLMOps), Optimization, Bayesian Methods, Time Series Analysis, Causal Inference | Experiment Tracking (MLflow, W&B), Versioning (DVC), Cloud ML Platforms (SageMaker, Azure ML, Vertex AI) |
| Programming & Systems | Databases & Visualization | ||
|---|---|---|---|
| Languages | Foundations | Databases | Visualization |
| Python, Scala (Functional), Rust, SQL, R, Haskell, Julia, Java, JS/TS, Bash/Zsh | Linux Systems (NixOS), Distributed Systems Concepts, Software Design | PostgreSQL, MySQL, MongoDB, Redis, DuckDB, ClickHouse | Power BI, Tableau, Superset, D3.js, React |