In this course, Python and data scientist Jesus Lopez focuses on practical time series analysis in Python, emphasizing explainability and discovering causal relationships. Discover methods for understanding why patterns emerge, what variables drive changes over time, and how to interpret results responsibly. All topics are taught through hands-on examples, mainly from the energy sector, so you can apply insights directly to real-world data. Build the understanding you need to transform raw time series data into meaningful explanations that inform strategic decisions.
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