• Training in Simulation Lab
• Code Your Own Strategies into Algos
• Training on industry leading algorithmic trading platforms
• CPD-accredited by LIBF: CPAT is officially CPD-accredited by LIBF (formerly the London Institute of Banking and Finance) under their prestigious Accredited CPD Programme initiative.

The IIQF’s Super Specialization AI Program focuses on AI and ML-driven risk management and modeling use cases across various types of risks.

• Focused learning journey to cover the AI & ML based models & analytics products for risk management sub-domains.
• Insightful coverage of quantitative risk modelling use of AI & ML techniques & algorithms within BFSI & Fintech space.
• Extensive coverage of the AI & ML adoption considerations, challenges & cautions - regulatory, policy, legal, compliance and ethical.
• Practical deep-dive into AI & ML driven risk models, methodology, & mechanics across supervised, semi-supervised & unsupervised learning regimes. Coverage of best quants modelling practices and research topics in risk management domain.
• Designed to deliver know-how on BFSI risk management use-cases & applications across portfolio/credit/market/operational risk analytics.
• Wider span coverage of financial use cases encompassing risk prediction, forecasting, anomaly detection, sentiment analysis & others.
• Rigorous live online classroom lectures from our expert faculty panel constituting BFSI industry subject matter experts & academic researchers
• Practical hand-on learning through Python prototyping & implementation workshops on front-to-back model building & algorithmic training exercises
• Renders technical know-how on BFSI & Fintech industry risk management application ecosystem - application architectural design & technology stack.
• BFSI industry mentor-led AI for Risk Management capstone projects and implementation white paper writing.

The IIQF's Super Specialization AI Program focuses on AI and ML-driven risk management and modeling use cases across various types of risks.

• Focused learning journey to cover the essentials on derivative products, derivative pricing framework & fair valuation principles.
• Insightful coverage of quantitative front-office and back-office valuation & pricing models for derivatives using AI & ML techniques & algorithms.
• Extensive coverage of the AI & ML adoption considerations, challenges & cautions - mispricing risk, pricing anomalies & disputes, pricing verifications etc.
• Practical deep-dive into AI & ML driven models, methodology, & mechanics across supervised & deep learning regimes. Coverage of best quants modelling practices and research topics in derivative valuations & pricing domain.
• Designed to deliver know-how on derivative risk analytics use cases encompassing high dimensional, simulation driven & non-linear problem sets.
• Rigorous live online classroom lectures from our expert faculty panel constituting BFSI industry subject matter experts & academic researchers.
• Practical hand-on learning through Python prototyping & implementation workshops on front-to-back model building & algorithmic training exercises.
• Renders technical know-how on BFSI & Fintech industry derivative solutions & application ecosystem - architectural design & technology stack.
• BFSI industry mentor-led AI for derivative valuation & pricing capstone projects and implementation white paper writing.