Statistică, învățare automată, AI generativ…
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Learners will understand the mathematical intuition behind core machine learning algorithms and implement basic predictive models in Python. By completing hands-on examples, learners will prepare data, train standard regression, classification, and clustering models, and evaluate their real-world performance.
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Learn to automate business workflows by building autonomous single- and multi-agent systems from the ground up. You will write foundational Python scripts, integrate APIs, orchestrate coordinated agent teams, and implement human oversight to handle real-world tasks reliably.
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By the end of this course, you will be able to analyze, summarize, and critique real-world datasets with confidence using fundamental statistical methods. You will learn to draw valid conclusions, detect misleading claims, and support everyday professional decisions with data.
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Learners will be able to organize, summarize, and visualize raw data, as well as critically interpret statistical claims and significance tests in professional and everyday contexts.
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Learn SQL from the ground up by writing real queries against realistic datasets, ending with the ability to independently retrieve, join, summarize, and analyze data to answer practical business questions.