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@@ -47,20 +47,22 @@ All the lectures and assignment templates are available for download through thi
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### Comparison to Computing in Context
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Both courses are intended for students who are new to coding. {{course_name}} can be thought of as a subset of [the SIPA sections of Computing in Context](https://computing-in-context.afeld.me/).
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Both courses are intended for students who are new to coding. {{course_name}} can be thought of as a subset of [the SIPA sections of Computing in Context](https://computing-in-context.afeld.me/). Computing in Context has more class time per week and goes a full semester, so it's more than 4x the class time of Python for Public Policy.
|**Meetings per week**| One 110-minute lecture | Two 75-minute lectures plus one 90-minute recitation|
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|**Meetings per week**| One 110-minute lecture |[Two 75-minute lectures plus one 90-minute recitation][cic-meeting]|
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|**Topics covered**| See [syllabus](syllabus.md#schedule)| See [syllabus](https://computing-in-context.afeld.me/#schedule)|
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|**Student body**| Mainly SIPA | Mix of SIPA and other schools|
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|**Student body**| Mainly SIPA |[Mix of SIPA and other schools][cic-structure]|
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|**Best suited for**| Students who just want a taste of coding | Students who are interested in coding being part of their lives/careers |
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|**Other differences**| We speed through Python fundamentals, spending most of the time on data analysis in Python. | <ul><li>Spends more time on Python fundamentals, such as control flow and functions.</li><li>[Required for the Data Science for Policy (DSP) Concentration.][dsp]</li><li>[Allows students to take more advanced DAQA courses.][cic-prereq]</li></ul> |
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