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## Data Science ML/AI Learning Paths
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# Take the LEAD with Datalab.
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## The Datalab _LEAD Program: Learn, Experience, Advance, Develop_.
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### Data Science ML/AI Learning Paths
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We present 12 topics in the data science learning path, providing learning objectives, related skills, subtopics, and references/resources for each. The goal is to give graduate students a structured and comprehensive program to acquire data science expertise, including hands-on experience with real-world open-source tools and libraries.
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### A. General Data Science
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:construction: :construction: :construction: :construction:
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#### A. General Data Science
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<!--
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[**A1: Introduction to Data Science and Machine Learning**](mlpaths/A1_Intro_to_DataScience_and_ML.md)
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### B. Statistics
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#### B. Statistics
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### C. Machine Learning
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#### C. Machine Learning
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### D. Deep Learning
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#### D. Deep Learning
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### E. Continuous Integration / Continuous Development
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#### E. Continuous Integration / Continuous Development
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***
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Created: 05/25/2025 (C. Lizárraga); Updated: 05/29/2025 (C. Lizárraga)
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<img src="https://upload.wikimedia.org/wikipedia/commons/thumb/a/a3/Cc.logo.circle.svg/64px-Cc.logo.circle.svg.png" width=20> 2025. [University of Arizona DataLab](https://datascience.arizona.edu/education/uarizona-data-lab), [Data Science Institute](https://datascience.arizona.edu/)
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<img src="https://upload.wikimedia.org/wikipedia/commons/thumb/a/a3/Cc.logo.circle.svg/64px-Cc.logo.circle.svg.png" width=20> 2025. [University of Arizona DataLab](https://datascience.arizona.edu/education/uarizona-data-lab), [Data Science Institute](https://datascience.arizona.edu/
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