Update the overall project info

README.md

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 # Ames Housing
 
-This repository is a case study of applying various machine learning models to
+This repository is a case study of applying various machine learning models
-the problem of predicting house prices.
+    to the problem of predicting house prices.
 
-The dataset is publicly available and can be downloaded, for example, at
+The dataset is publicly available
-[Kaggle](https://www.kaggle.com/c/house-prices-advanced-regression-techniques).
+    and can be downloaded, for example, at [Kaggle](https://www.kaggle.com/c/house-prices-advanced-regression-techniques).
 
 The case study is based on this [research paper](static/paper.pdf).
 
+A video presentation of the case study is available on [YouTube <img height="12" style="display: inline-block" src="static/link/to_yt.png">](https://www.youtube.com/watch?v=VSeGseoJsNA).
+
+
+### Table of Contents
+
 The analyses are presented in four notebooks that may be interactively worked
 with by following these links:
-- [Data Cleaning](https://mybinder.org/v2/gh/webartifex/ames-housing/master?urlpath=lab/tree/01_data_cleaning.ipynb)
+- *Notebook 1*: [Data Cleaning](https://mybinder.org/v2/gh/webartifex/ames-housing/main?urlpath=lab/tree/01_data_cleaning.ipynb)
-- [Correlations](https://mybinder.org/v2/gh/webartifex/ames-housing/master?urlpath=lab/tree/02_pairwise_correlations.ipynb)
+- *Notebook 2*: [Correlations](https://mybinder.org/v2/gh/webartifex/ames-housing/main?urlpath=lab/tree/02_pairwise_correlations.ipynb)
-- [Visualizations](https://mybinder.org/v2/gh/webartifex/ames-housing/master?urlpath=lab/tree/03_descriptive_visualizations.ipynb)
+- *Notebook 3*: [Visualizations](https://mybinder.org/v2/gh/webartifex/ames-housing/main?urlpath=lab/tree/03_descriptive_visualizations.ipynb)
-- [Predictions](https://mybinder.org/v2/gh/webartifex/ames-housing/master?urlpath=lab/tree/04_predictive_models.ipynb)
+- *Notebook 4*: [Predictions](https://mybinder.org/v2/gh/webartifex/ames-housing/main?urlpath=lab/tree/04_predictive_models.ipynb)
-
-A video presentation of the case study is available on
-    [YouTube <img height="12" style="display: inline-block" src="static/link/to_yt.png">](https://www.youtube.com/watch?v=VSeGseoJsNA).
 
 
-## Installation
+### Objective
 
-The project can be cloned and may be worked with under the MIT open source
+The **main goal** is to **show** students
-license.
+    how **Python** can be used to solve a typical **data science** task.
-Python 3.7 was used to prepare and test the provided code.
-Albeit the [poetry](https://python-poetry.org/) tool was used to manage the
-dependencies, a [requirements.txt](requirements.txt) file is also provided as
-an alternative.
 
-On a Unix system, run:
-- `git clone https://github.com/webartifex/ames-housing.git` (or use HTTPS
-   instead)
-- either `poetry install` or `pip install -r requirements.txt` (in the latter
-  case, it is suggested that a virtual environment be used)
-- after installation, `jupyter lab` opens a new tab in one's web browser where
-  the notebooks and data files may be opened
 
-Alternatively, the project should also be runnable with the
+### Prerequisites
-[Anaconda Distribution](https://www.anaconda.com/products/individual).
+
+To be suitable for *beginners*, there are *no* formal prerequisites.
+It is only expected that the student has:
+- a *solid* understanding of the **English** language and
+- knowledge of **basic mathematics** from high school.
+
+Some background knowledge in Python is still helpful.
+To learn about Python and programming in detail,
+    this [introductory course <img height="12" style="display: inline-block" src="static/link/to_gh.png">](https://github.com/webartifex/intro-to-python) is recommended.
+
+
+### Getting started & Installation
+
+To follow this workshop, an installation of **Python 3.8** or higher is expected.
+
+A popular and beginner friendly way is
+    to install the [Anaconda Distribution](https://www.anaconda.com/products/individual)
+    that not only ships Python itself
+    but also comes pre-packaged with a lot of third-party libraries
+    including [Python's scientific stack](https://scipy.org/about.html).
+
+Detailed instructions can be found [here <img height="12" style="display: inline-block" src="static/link/to_gh.png">](https://github.com/webartifex/intro-to-python#installation).
+
+
+## Contributing
+
+Feedback **is highly encouraged** and will be incorporated.
+Open an issue in the [issues tracker <img height="12" style="display: inline-block" src="static/link/to_gh.png">](https://github.com/webartifex/ames-housing/issues)
+    or initiate a [pull request <img height="12" style="display: inline-block" src="static/link/to_gh.png">](https://help.github.com/en/articles/about-pull-requests)
+    if you are familiar with the concept.
+Simple issues that *anyone* can **help fix** are, for example,
+    **spelling mistakes** or **broken links**.
+If you feel that some topic is missing entirely, you may also mention that.
+The materials here are considered a **permanent work-in-progress**.
 
 
 ## About the Author
 
-Alexander Hess is a PhD student at the Chair of Logistics Management at the
+Alexander Hess is a PhD student
-[WHU - Otto Beisheim School of Management](https://www.whu.edu) where he
+    at the Chair of Logistics Management at [WHU - Otto Beisheim School of Management](https://www.whu.edu)
-conducts research on urban delivery platforms and teaches an introductory
+    where he conducts research on urban delivery platforms
-course on Python (cf., [Fall Term 2019](https://vlv.whu.edu/campus/all/event.asp?objgguid=0xE57C2715B01B441AAFD3E79AA05CACCF&from=vvz&gguid=0x6A2B0ED5B2B949E69957A2099E7DE2F1&mode=own&tguid=0x3980A9BBC3BF4A638E977F2DC163F44B&lang=en),
+    and teaches coding courses based on Python in the BSc and MBA programs.
-[Spring Term 2020](https://vlv.whu.edu/campus/all/event.asp?objgguid=0x3354F4C108FF4E959CDD692A325D9AFE&from=vvz&gguid=0x262E29795DD742CFBDE72B12B69CEFD6&mode=own&lang=en&tguid=0x2E4A7D1FF3C34AD08FF07685461781C9)).
-
-Connect him on [LinkedIn](https://www.linkedin.com/in/webartifex).
 
+Connect with him on [LinkedIn](https://www.linkedin.com/in/webartifex).

static/link/README.md

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+This folder contains small images
+that are used to enhance the links in the notebooks and markdown files.