Benefits and Challenges #riskawarenessweek2019 RISK-ACADEMY Blog

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Наши популярные онлайн курсы

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Риск-ориентированное управление. Самостоятельно

Курс направлен на развитие навыков риск-ориентированного мышления, которое позволяет выявлять, приоритезировать и моделировать влияние рисков на ключевые цели или решения организации.

25000 руб
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Риск-ориентированное управление. С преподавателем.

Крупнейшая в России программа онлайн-подготовки к двум сертификациям: национальной и международной G31000

45000 руб
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Количественная оценка рисков

Единственный в России и СНГ онлайн-курс по количественной оценке рисков и принятию решений.

33000 руб

Nowadays the quantitative risk analysis approaches in various fields are widely used at different business case stages: geology, engineering, construction and operations. You have probably heard of the QRA, Cost and Schedule Risk Analyzes, Reliability and Availability Modeling, Reliability Centered Maintenance etc., which have shown their value, added at different stages. These methods are aimed at improving the decision quality (DQ).

RISK AWARENESS WEEK 2019 broadcasted online at https://2019.riskawarenessweek.com from 14 to 18 October 2019

However, classically these methods give recommendations to decision makers with some delay, and sometimes it even happens that the recommendations are not relevant. Given the reduction in cost of the real-time data extraction, transmission and processing infrastructure, the risk analysis toolset has received a new set of characteristics that significantly improve several stages of DQ.

Within this workshop, speaker will demonstrate theoretical and practical benefits, challenges of machine learning in real-time risk analysis. Speaker also will present the machine learning use case at the refining process allowing in real time to eliminate the HSE risk and increase operational efficiency.

This is a must watch session for anyone working in risk management and a great foundation for the whole week. Make sure you sign up!

About Damir

Damir Ramazanov has practiced different quantitative analysis and risk modeling approaches for over 15 years mainly in oil & gas, power generation and mining & metal industries at different business case stages (from FEL1 to operations). He has MSc in O&G Operations (Ufa State Petroleum Institute, 2005), PhD on quantitative risk modeling of the enhanced oil recovery projects (Russian Academy of Science, 2010), MBA Big Data & Business Analytics (Amsterdam Business School, University of Amsterdam, 2019), certificates PMI-RMP and PMI-PMP. He currently holds the position of Group Project Risk Manager at ERG Group HQ and supports C-executives on risk-informed decisions on portfolio, program and project levels. Prior to joining ERG, he worked as a chief economist in Russian-Swiss JV on Oil Exploration, consulting company, a risk manager in Bashneft, a head of downstream risk management division in Gazpromneft, risk management lead in Lukoil Overseas and Lukoil International Upstream East. Interests: Data Science, Decision Analysis, Business Risk Modeling, Data-Driven Management, Project Management