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[github.com/jtkiley](https://github.com/jtkiley/)
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:::
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## Related
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- CARMA 2020 (overlaps with this course): Introduction to Python and Content Analysis of Text. ([Github](https://github.com/jtkiley/2020_carma_python))
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- Seminar materials (overlaps with this course): Text Analysis: Planning to Publication. ([Github](https://github.com/jtkiley/text_seminar))
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- Text analysis and machine learning workshop at WU (Oct. 2018) and RSM (Oct. 2019).
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- AOM Big Data workshop with Tim Hannigan, Hovig Tchalian, and Laura Nelson. ([Github](https://github.com/jtkiley/curation_workshop))
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## Course Agenda
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- Tools: Python, packages and environments
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- Basics: Python syntax and conventions, Jupyter Notebooks
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- Data handling and project planning
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- Data gathering and assembly
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# Overview
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## Overview
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- Resources for learning.
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- A brief R comparison.
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# What do I really need to know about Python?
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## Why Python?
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- Learning resources: wide popularity in academia and practice means that there are extensive resources.
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- Scalability: from your computer, to the cloud, to a computing cluster, you can use largely the same tools.
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