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UTEXAS Curriculum

What Makes us Different?

UTEXAS Energy is dedicated to developing both fundamental energy expertise and hands-on skills in energy-related projects, including proficiency in Python and other software commonly used on the trading floor.

UT Energy Python Curriculum

Week 1: Setup

  • Introduce students to the course and expectations.

  • Create a Python environment and run the "Hello World" program.

Week 2: Functions & Data Structures

  • Discuss the basics of functions and data structures

  • Introduce students to the different types of data structures, such as lists, arrays, dictionaries, and sets

  • Practice working with data structures in Python

  • Kaggle & Other Resources to find data

​Week 3: Read & Write to CSV’s, Files, Pandas, ...

  • Explain how to read and write data to CSV files.

  • Introduce students to the Pandas library and how to use it to read and write dataframes.

  • Visualize data

  • Practice working with CSV files and Pandas in Python.

​Week 4: Big Data Project Part 1: Load Dataset & Start Feature Engineering

  • Load a real-world dataset into Python.

  • Start to explore the data and perform some basic feature engineering.

  • Discuss the challenges of working with big data.

Week 5: Big Data Project Part 2: Make a Prediction & Talk about how to extend further

  • Develop a model to make predictions on the data.

  • Evaluate the performance of the model.

  • Discuss how to extend the project further, such as by adding new features or using a

    different machine learning algorithms.

Week 6: Project Presentations

  • Present your projects & get real-time feedback! 

  • Learn how you can further progress in the field! 

UT Energy Trading Curriculum

Week 1 & 2: Crude Oil

  • Overview of the crude oil supply chain – from upstream extraction to downstream refining.

  • Key global producers and importers (OPEC, U.S., China, India) and benchmarks (WTI vs. Brent).

  • Factors impacting price (geopolitics, inventories, production cuts, demand cycles).

Week 3: Refined Products (Gasoline/Diesel)

  • Crude oil refining process and refinery economics (crack spreads, margins).

  • Seasonal demand patterns (e.g., summer driving season) and regulatory impacts.

  • Pricing mechanisms and logistics (RINs, blending mandates, pipeline constraints).

​ Week 4: Natural Gas/LNG + Case Competition Prep

  • U.S. natural gas fundamentals: shale production, storage, seasonality.

  • LNG export markets: major players, pricing hubs (Henry Hub vs. JKM vs. TTF).

  • Mock trading scenario or case prep: use S&D inputs to justify a trading position.

Week 5: NGLs (Butane, Ethane, Propane, etc.)

  • Difference between natural gas and NGLs; extraction via gas processing plants.

  • End uses: petrochemicals, home heating, fuel blends – and their price links to crude/gas.

  • Major players in the U.S. midstream space and international trade flows.

Week 6: Power / Electricity

  • Power grid basics: generation types (thermal, renewable), ISO/RTO structure.

  • Concepts like locational marginal pricing (LMP), congestion, and load forecasting.

  • Deregulated vs. regulated markets – and how traders arbitrage price spreads

Week 7: Metals (Gold, Silver, Copper, Lithium)

  • Use cases: copper for infrastructure, lithium for EVs, gold/silver as monetary hedges.

  • Supply chain dynamics and major mining regions (e.g., Chile, Australia, Congo).

  • Macroeconomic influences (interest rates, inflation, China growth) on metal prices.

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