How use Power Bi and Excel For Oil&Gas Forecasting
This course use artificial intelligence to built up some content.
What you’ll learn
- Analize Oil&Gas Data production with Excel and PowerBi.
- Data Assumption and integration.
- A Machine Learning Model to predict future Oil&Gas Price.
- A casy of study from Permian Basin : Forecasting Price.
Course Content
- Introduction –> 3 lectures • 53min.
- A casy of study from Permian Basin : Forecasting Price –> 1 lecture • 8min.
- A Machine Learning Model to predict future Oil&Gas Price –> 1 lecture • 3min.
Requirements
This course use artificial intelligence to built up some content.
Elevate your analytical skills with this deep-dive course focusing on Oil & Gas price analysis, integrating the power of Excel, Python, and Power BI. In today’s volatile energy market, the ability to rapidly process, model, and visualize commodity prices (Crude, Gas, and refined products) is crucial for strategic decision support. You will begin by mastering Excel for fundamental data hygiene, employing advanced functions, PivotTables, and conditional formatting to cleanse and structure complex historical pricing and inventory data . Next, the course transitions to Python, where you’ll utilize industry-standard libraries like Pandas and NumPy for data wrangling data model for building time-series forecasting models, such as ARIMA or simple regression, based on leading market indicators. The focus here is on understanding model assumptions and validating results. Finally, you will integrate these models and data into Power BI to design sophisticated, interactive dashboards . You’ll learn DAX essentials and create visuals that track volatility, compare current prices against forecasts, and highlight regional market spreads, allowing for clear and persuasive communication of complex market intelligence to stakeholders. By the end of this program, you will possess a complete, end-to-end workflow, enabling you to transform raw data into actionable insights and confidently navigate the dynamics of the global energy trading landscape.