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slight improvement of lecture structure
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_quarto.yml

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href: assignments/assignment-1.qmd
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- text: "02 Assignment"
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href: assignments/assignment-2.qmd
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- text: "FAQs"
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href: general/faq.qmd
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- text: "Cheatsheet"
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- text: "FAQs"
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- text: "Literature"
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general/syllabus.qmd

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# Part II
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## Data Science with Python
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In the second part, we will cover basic data science tools in Python referring to data manipulation, descriptive and explorative analysis as well as visualization. At the end, an outlook will be provided on the next steps in Python, including statistical analysis and machine learning.
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In the second part, we will cover basic data science tools in Python referring to data manipulation, descriptive and explorative analysis as well as visualization. At the end, an outlook will be provided on the next steps in Python.
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## Lectures
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**Using Modules and Packages (VI)**\
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Standard libraries, random numbers and how to use them
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**NumPy and Pandas for Scientific Computing (VII)**\
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Data manipulation with Pandas, array operations with NumPy
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**NumPy for Scientific Computing (VII)**\
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Fast array operations with NumPy
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**Plotting Data (VIII)**\
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Matplotlib, Seaborne based on hand-on examples
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**Pandas and AI (VIII)**\
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Pandas for data manipulation, AI with Cursor
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**First steps into A.I. (IX)**\
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A brief intro to machine learning concepts
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**Plotting Data (IX)**\
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Matplotlib with AI based on hand-on examples
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# Part III
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## Programming Projects

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