move content

content/docs/modules/prep/_index.md

@@ -7,13 +7,37 @@ bookCollapseSection: false
 
 # Preparation before the course starts
 
-In this class, you'll learn the basics of Python, and how to use it to collect data from the internet.
+Obtaining data via web scraping and APIs isn't usually something you do "in your browser". Certainly for continuous data collections, a *local* setup is required. That's why you need to install software on your computer before you can get started. All the software used in this class is available open source, i.e., you don't need to pay for it.
 
 It's important to spend some time *before the beginning of the class* to install the required software, and familiarize yourself with Python.
 
-{{< button relref="../../../docs/tutorials/software" >}}Get started now!{{< /button >}}  
+### 1) Install Python via Anaconda
+
+Please follow the installation guide for [Python via Anaconda](https://tilburgsciencehub.com/get/python).
+
+{{< button href="https://tilburgsciencehub.com/get/python" >}}Start the installation now!{{< /button >}}
+
+{{< hint info >}}
+**Tips**
+- The installation of Anaconda can **easily take half an hour**! Please install it before the start of the class, and ensure you have administrator rights.
+- We recommend installing the Anaconda Individual Edition (Anaconda 64-Bit Graphical Installer; version 3.9), which you find [here](https://www.anaconda.com/products/distribution). Make sure to select the __correct package for your operating system.__
+- In the tutorial (at 2:23), we open the Command Prompt. On Mac, this program is called Terminal (for more information see [this](https://generalassembly.github.io/prework/cl/#/) interactive walkthrough - optional).
+
+{{< /hint >}}
+
+### 2) Obtain access to Premium Content at Datacamp.com
+
+We use material provided by Datacamp.com that otherwise is only available via paid premium subscriptions. Students can use this material with their @tilburguniversity.edu account for free.
+
+{{< button href="/docs/course/support/datacamp/" >}}Unlock Premium content now!{{< /button >}}
+
+
+### 3) Getting to know Python
+
+Eager for more? You can already follow the introduction course to Python on Datacamp, __chapters 1-3__. Novices will need about 3-4 hours. If you don't have the time, don't worry. In your first course week, we have set aside some time to work through the tutorial and exercises.
+
+{{< button href="https://datacamp.com/courses/intro-to-python-for-data-science" >}}Start your first tutorial on Datacamp.com now!{{< /button >}}
 
-{{< datacamp >}}
 
 <br>
 <div style="text-align: right">{{< button relref="week1" >}}Next week{{< /button >}}</div>

content/docs/modules/week1/_index.md

@@ -14,11 +14,27 @@ bookCollapseSection: false
 {{% laptop %}}
 - Introduction to the course ([slides](slides.html)) <!-- add link ([re-watch](https://youtu.be/b3Fiq3mrsb4))add zoom link-->
 - Brainstorm for ground-breaking data collections
-- [Tutorial: Python bootcamp for web data](docs/tutorials/pythonbootcamp)
+- Tutorial: Python bootcamp for web data ([download](pythonbootcamp/python-bootcamp-in-class.ipynb), [Google Colab](https://colab.research.google.com/github/hannesdatta/course-odcm/blob/master/content/docs/modules/week1/pythonbootcamp/python-bootcamp-in-class.ipynb), [Learning goals](pythonbootcamp/))
+
+
+
+{{% hint info %}}
+__Downloading to and starting the tutorial on your computer__
+
+- Right-click on the download link and select "download linked file as...)".
+- Move the file to a convenient file location (e.g., somewhere in your course folder)
+- If the downloaded file is a `.zip` (compressed) file, unzip it.
+- Open Jupyter Notebook (e.g., using the terminal or the Anaconda Navigator), navigate to the folder where you stored the downloaded files, and open the `.ipynb` file from within Jupyter Notebook.
+- Start with the tutorial!
+{{% /hint %}}
+
+
 
 ## Self-study and activities
 
-- Exercises after class
+- After-class exercises on Datacamp.com (about 3 hours; [work on the first three chapters only](https://datacamp.com/courses/intro-to-python-for-data-science))
+
+{{% datacamp %}}
 
 
 <!--

content/docs/modules/week1/pythonbootcamp/_index.md

@@ -0,0 +1,24 @@
+---
+weight: 20
+title: Python Bootcamp
+description: Learn the basics on how to retrieve web data using Python
+bookCollapseSection: false
+bookHidden: true
+---
+
+# Tutorial: Python Bootcamp for Collecting Web Data 
+
+## Learning goals
+
+* Locally launch Jupyter Notebook and Spyder
+* Know when it's useful to use Google Colab in the cloud
+* Understand basic programming concepts and their applications to collecting web data
+
+
+<!--
+
+If you're new to Python, please work through the first 3 chapters of the Introduction to Python Datacamp course.
+
+You need to have an understanding of variables, lists, and functions. In class, you already practiced with loading a Jupyter Notebook and perform basic operations in Python. 
+
+-->

content/docs/modules/week1/pythonbootcamp/odcm.txt

@@ -0,0 +1,2 @@
+Learn how to mine the web
+Welcome to the course website of oDCM. This course teaches you the nuts and bolts about collecting data from the web. Unlike most other courses on this topic, this course not only teaches you the technicalities of using web scraping and Application Protocol Interfaces (APIs), but also introduces a comprehensive framework that helps you to think about scraping - specifically with regard to its application in academic marketing research.