Fsdss 563 Official

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| Week | Module | Key Topics | What You’ll Be Able To Do | |------|--------|------------|----------------------------| | 1‑2 | | Market microstructure, alternative data sources, data acquisition APIs (Bloomberg, Refinitiv, Tiingo). | Pull, clean, and store heterogeneous financial data at scale. | | 3‑4 | Statistical Modeling for Finance | Time‑series econometrics, GARCH, copulas, regime‑switching models. | Build robust predictive models that respect market dynamics. | | 5‑6 | Machine Learning & AI for Trading | Gradient boosting, LSTM/Transformer models, reinforcement learning, model interpretability (SHAP, LIME). | Deploy AI models that generate alpha while staying explainable. | | 7‑8 | Secure Data Pipelines | Encryption (AES‑256, homomorphic), tokenization, secure multi‑party computation (SMPC). | Design end‑to‑end pipelines that keep data confidential. | | 9‑10 | Cloud & Real‑Time Architecture | Kubernetes, Kafka, Flink, serverless functions, cost‑optimization. | Build resilient, low‑latency systems for live‑trading environments. | | 11‑12 | Compliance & Ethical AI | FDPA 2025, GDPR/CCPA, fairness metrics, bias mitigation. | Conduct audits, generate compliance reports, and embed ethics. | | 13‑14 | Capstone Project & Presentation | Full‑stack solution to a real‑world problem (e.g., fraud‑detection engine). | Deliver a production‑ready, secure AI system with documentation. | fsdss 563

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