Data Science for Energy Risk Managers & Trading Professionals
Data Science for Energy Risk Managers
Machine learning and other forms of automation are transforming the way energy firms are analysing data to gain a competitive advantage.
Join us for this innovative and practical two day training course led by Nima Safaian, head of trading analytics at Cenovus Energy, which will provide a comprehensive introduction to data science for energy risk managers and trading professionals.
The course has been designed to be hands-on and interactive, participants will be given the opportunity to follow the course material and try out the examples in real time with guidance from the course tutor.
What will you learn?
- Learn about real life data science examples for risk managers and trading analysts
- An introduction to the data science R ecosystem
- Creating and deploying interactive reports and apps using Shiny
- Basics of machine learning for risk managers and more advanced concepts in deep learning and analytics using big datasets
- Learn tidyverse and other data wrangling tools
- Approaches to data visualisations and developing automated and interactive analytics
Who should attend
Relevant departments may include but are not limited to:
- Quantitative analysis
- Risk management
- Data science
- Machine learning
- Trading analysis