<aside>
This curriculum is designed to equip participants with the skills and knowledge necessary for addressing critical issues in carbon budgeting, renewable energy potential analysis, and power capacity expansion planning, providing a blend of theoretical and practical learning across three key modules.
Our program runs from April 2025 to November 2025, offering three terms that cover:
Modelling Basics with Python: National Allocation of the Global Carbon Budget [Applications are closed]
Power and Energy System Modeling with Python: A Beginner’s Guide for Long-Term Capacity Expansion Planning
Solving Real-World Energy Challenges with GIS: Lessons from Case Studies
Head master: Sanghyun Hong (PLANiT)
Email: [email protected]
Slack channel: https://planitinstitute.slack.com/archives/C086TGBD14L </aside>
This beginner-friendly program is for non-profit climate impact practitioners in Asia looking to gain understanding of modelling concepts and Python programming. The program provides hands-on workshops on global carbon budget allocation model using real-world data. Through a combination of engaging lectures, workshops, and collaborative group project, participants will learn essential concepts and tools for data-driven decision-making. Two special guest lecturers will also provide practical insight on how modelling is used to evaluate ESG evaluation and climate justice litigation. By the end of the course, participants will have obtained basic data analysis skills in Python and understanding of how modelling techniques can be used to create real-world impact.
#BasicPython #DataAnalysis #CarbonBudgets #ClimateRiskModelling
Applications: Submit by March 14th ▶️ https://forms.gle/sZcs994U6nqJou3g8
Prerequisites: Interest in climate policy and data analysis, commitment to attend all sessions, access to a laptop with Python installed
Lecturers: Sanghyun Hong (PLANiT), Uni Lee (Ember & PLANiT), Joowon Kwon (PLANiT), Sejong Yoon (PLAN 1.5)
Certificates: Fundamentals of Data Analysis and Modelling with Python
Modelling Basics with Python: National Allocation of the Global Carbon Budget
This course is designed to provide participants with a comprehensive introduction to energy and environmental modelling, with a focus on practical applications in policy and decision-making. It bridges foundational concepts and advanced techniques, equipping participants with the skills to develop and analyze energy models for real-world scenarios.
Key topics include optimization using Pyomo, simulation dynamics for industrial decarbonization, and power system modelling with PyPSA. Through engaging lectures, hands-on workshops, and group projects, participants will learn to construct and interpret models for long-term capacity expansion planning, scenario analysis, and industrial decarbonization strategies.
By the end of the course, participants will have a strong understanding of energy modelling tools and techniques, enabling them to address complex energy policy challenges and contribute to sustainable energy transitions.
Prerequisite: Basic knowledge of Python and energy systems is recommended. Lecturers
Lecturer: Sanghyun Hong (PLANiT), Uni Lee (Ember & PLANiT), Jinsu Park (PLANiT), Saerok Jeong (University of Chicago)
Certificates: Fundamental in Power Modelling