Deep Learning for time-series forecasting on Carbon Dioxide

Use Machine Learning methodologies in Python - a step by step methodology for accurate forecasts

Created by: Dr.S. Giannelos
Quantitative Energy Expert | Data Science, ML & Optimization

What Will I Learn?

• TYPE THIS code where it says 'Apply Code' (remove spaces): FF25DD92FAF 0A68B4586
• All the code, is available for you to download! Plus: publications and tutorials!
• YOU WILL LEARN how to develop deep learning models for time-series forecasting of CO2 emissions. The real-world model is developed in Python.
• FAST HELP WITHIN HOURS: Have questions or need guidance? Send a message and get a response within hours!
• Get 50% at the Quant Energy Academy: www [ dot ] quantenergyacademy [dot] com. Use code UDEMY50.

Requirements

• There are no prerequisites except basic knowledge of Python

Target audience

• Quantitative Developers expanding into economics with a focus on energy
• Energy Professionals interested in data‐driven methods
• Finance & Economics professionals looking for economics-related data science skills
• Data Scientists / Machine Learning Engineers applying skills in economics focused on energy
• Students & Researchers looking for practical projects
• Managers wanting to understand Data Science and Machine Learning applications in economics
• Operational researchers and economics/energy modellers interested in advancing their skills