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Course Description

This course introduces the foundations of data analytics and visualization for carbon management decision-making. Designed for professionals in the energy and policy sectors, it focuses on practical skills for interpreting carbon data and communicating insights effectively. You will work hands-on with realistic emissions datasets using Power BI to load, model, analyze, and visualize carbon information. Through a series of scaffolded, applied activities, you will build a decision-focused dashboard that highlights emissions trends, comparisons, and net emissions impacts. The course emphasizes learning by doing, with each module contributing directly to a final, workplace-relevant deliverable. By the end of the course, you will be equipped to use data analytics tools to support evidence-based carbon management decisions, improve reporting clarity, and add analytical value in sustainability-focused roles. Learning Outcomes Upon completion of this course, you will be able to: Frame a structured carbon analytics question set and data model that supports decision-making. Build and validate an initial Power BI emissions report page. Prepare and evaluate a multi-table Power BI data model. Clean and standardize carbon-related datasets in Power Query. Building the carbon star schema model and validating relationships. Design and validate DAX measures that accurately calculate emissions, offsets, net emissions, and time-based comparisons. Develop a carbon analytics dashboard that communicates emissions insights clearly, supports user-driven exploration, and demonstrates quality assurance and design reasoning.

Applies Towards the Following Certificates

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Enrol Now - Select a section to enrol in

Section Title
Data Analytics and Machine Learning for Carbon Management
Type
Internet Paced - Online Asynchronous
Dates
Nov 09, 2026 to Nov 29, 2026
Course Fee(s)
Contract Fee non-credit $0.00
Section Title
Data Analytics and Machine Learning for Carbon Management
Type
Internet Paced - Online Asynchronous
Dates
Nov 11, 2026 to Nov 20, 2026
Course Fee(s)
Contract Fee non-credit $0.00
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