finished unit 2

95d6ed7e · Felix Nyffenegger · 097d5593 · 95d6ed7e · 95d6ed7e · 95d6ed7e
Commit 95d6ed7e authored 6 months ago by Felix Nyffenegger
--- a/unit-1/introduction.ipynb
+++ b/unit-1/introduction.ipynb
@@ -191,8 +191,9 @@
    "   * Most of the documentaiton and examples you find are in English anyway\n",
    "   * We plan to offer this course to incomming exchange students\n",
    "4. There are tons of material to read, learn, and get support online\n",
-    "   * Most of the time this course refers to: https://www.w3schools.com/\n",
+    "   * Most of the time this course refers to: https://docs.python.org/3/ and https://www.w3schools.com/\n",
-    "   * It's simple, complete, and it looks the same for many programming languages "
+    "   * The fist is comprehensive and accurate to the latest standard\n",
+    "   * The second one is simple, sets focus on the basics, and it looks the same for many programming languages "
   ]
  },
  {

 %% Cell type:markdown id: tags:
 # Introduction to Python for Engineers
 ## Agenda
 - [Where do we start?](#where-do-we-start)
 - [An Example of a Python Program](#an-example-of-a-python-program)
 - [Background and History of Python Programming Language](#background-and-history-of-python-programming-language)
 - [About this Course](#about-this-course)
 - [Lession 1: Introduction to Jupyter Notebook](#lesson-1)
 %% Cell type:markdown id: tags:
 # Where do we start?
 Let's do a short Poll to see what you alredy know about Python.
 1. I have never used Python before.
 1. I have used Python before, but I am not very familiar with it.
 1. I have used Python before and I am somewhat familiar with it.
 1. I am a Python expert.
 %% Cell type:markdown id: tags:
 # An Example of a Python Program
 Below you see an example of a python program.
 If you are used to other programming languages, this looks a bit different... but you'll get used to it!
 %% Cell type:code id: tags:
 ``` python
 print('Python is fun!')
 ```
 %% Cell type:code id: tags:
 ``` python
 for g in range(3, 0, -1):
    print(g)
 ```
 %% Cell type:markdown id: tags:
 As you can see python is easy to read, almost like English. You will learn more about the Python syntax, later on.
 %% Cell type:markdown id: tags:
 # Background and History of Python Programming Language
 %% Cell type:markdown id: tags:
 ## Why Python?
 Python is a very popular programming language for a variety of reasons
 * **Readability and Simplicity**: Python has a clean and readable syntax, which makes it easy to learn and understand.
 * **Versatility**: Python is a general-purpose language, meaning it can be used for a wide range of applications, from web development to data analysis, machine learning, automation, and more. (e.g. our PLM System "CIM Database" is written in Python)
 * **Large Standard Library**: Python comes with a vast standard library that provides modules and functions for many common tasks, reducing the need for external libraries.
 * **Extensive Ecosystem**: There is a rich ecosystem of third-party libraries and frameworks that extend Python’s capabilities across different domains.
 * **Community Support**: Python has a large and active community, which means extensive documentation, a wealth of tutorials, and community-contributed packages are readily available.
 * **Cross-Platform Compatibility**: It can run on various operating systems like Windows, macOS, and Linux without modification.
 * **Data Science and Machine Learning**: Python has become the go-to language for data science and machine learning, largely due to libraries like NumPy, Pandas, Scikit-learn, and TensorFlow.
 %% Cell type:markdown id: tags:
 ## Background and History of Python Programming Language
 Let's trace the roots of this programming language
 * https://www.youtube.com/watch?v=Tm5u97I7OrM
 * https://www.youtube.com/watch?v=ucD_1ryKKm0
 * https://www.youtube.com/watch?v=J0Aq44Pze-w
 %% Cell type:markdown id: tags:
 ## Different Ways to use Python
 * **Python in "Jupiter Notebooks"**: This slide you see is a document, called Jupiter Notebook. It combines text / documentation with coding. In every code cell we can execute some python. All cells know of each other. This is a very convenient way do data analytics, since you can explain your thoughts, run your code, and visualize the results at the same place.
 * **Standalone Python Applications**. You write your code in an IDE such as VS-Code and execute it. There many different types of applications, such as web-applications, command line applications, or applications with a user interface that runs on your operating system.
 * **Micro-Python**: This is a subset of Python to write code, that runs on micro-controllers. This is becoming more and more popular for prototyping IoT applications. However, in terms of speed, it cannot compete with C/C++.
 * **Python Scripting**: And many software systems use Python as a scripting language to enhance its functionality (like our PLM solution at OST, or AWS Lambda Functions)
 %% Cell type:markdown id: tags:
 # About this Course
 %% Cell type:markdown id: tags:
 ## Some Comments Upfront
 1. The goal of this course is a dedicated introduction to the programming language for engineers
   * Basic usage of the language
   * Crunching data and connecting from different sources
   * Dealing with math and visualization
 2. With 2 ECTS we can only scrath at the surface
   * We will give you a lot of hints where you can do a deep dive yourself
   * If you want to become a programmer: you need to programm, A LOT!
   * We highly recommend to to give yourself challanges (AI is a good source to find ideas on how you can challange yourselg)
 3. Language: This course is in English language
   * Most of the documentaiton and examples you find are in English anyway
   * We plan to offer this course to incomming exchange students
 4. There are tons of material to read, learn, and get support online
-   * Most of the time this course refers to: https://www.w3schools.com/
+   * Most of the time this course refers to: https://docs.python.org/3/ and https://www.w3schools.com/
-   * It's simple, complete, and it looks the same for many programming languages
+   * The fist is comprehensive and accurate to the latest standard
+   * The second one is simple, sets focus on the basics, and it looks the same for many programming languages
 %% Cell type:markdown id: tags:
 ## Content of this Course
 1. The basics (Week 1-4)
   * Working with Jupiter Notebooks and VS-Code
   * Python syntax, data types, and control structures, loops
   * Functions, namespaces, and libraries
 2. Working with data (Week 5-7)
   * Extended list types: dictionary, tuples, sets
   * Crunching strings
   * Reading and writing files
 3. Dedicated libraries for engineers (Week 8-10)
   * Pandas
   * NumPy
   * MathPlot
 4. Advanced programming skills (Week 11-14)
   * Using webservices
   * Object oriented programming with Python
 You will find all required links on Moodle. And all lecture notebooks can be accessed here:
 https://gitlab.ost.ch/edu-public/python-for-engineers/pyeng-lectures
 %% Cell type:markdown id: tags:
 ## About coding and AI in this course
 * AI and co-pilots are great tools! I use them a lot for programming, it makes me faster
 * At these days, we cannot trust into AI.
    * Sometimes it does not understand the problem, your are trying to solve,
    * sometimes it just makes things up that that do not exist
    * AI has become a problem in cyber security
 * Thus, AI is only a helpful tool, if you can understand the output of it
 * When using AI, make sure you know what you are doing.
 **If you are new to a langugage don't use co-pilots. You need to get familiar with the syntax and you need to figure out how to use the language yourself**
 Remark, this Video explains very well, what you should consider when learning Python, and how to use/not use AI/Co-Pilots: https://www.youtube.com/watch?v=St48epdRDZw
 %% Cell type:markdown id: tags:
 ## Our Development Environment
 * In this course we use **Visual Studio Vode** as our IDE (most of you should be familiar with this)
 * Most of the exercises will be done on **Jupiter Notebook**
 * All templates and exercises are deliveres thoroug **gitlab**: https://gitlab.ost.ch/edu-public/python-for-engineers/pyeng-exercises
 * We highly encourage you to store your code in a personal ***git repository***!
  * This is the way programmers work, and you won't loose your code
  * If you want support, this is the best way to share code with us (I will not accept python files via email)
  * For those who don't know git, go here: https://www.youtube.com/watch?v=r8jQ9hVA2qs
 * In class we are working with **Python version 3.7**
 * Feel free to use your own device and upgrade to version **3.12**. However, we will not support or assist with private installations.
 %% Cell type:markdown id: tags:
 # Lesson 1: Introduction to Jupyter Notebook
 %% Cell type:markdown id: tags:
 ## About Jupyter Notebook
 * As mentioned before Jupyter Notebooks are a great way to program, explain, document and present results all in one place.
 * Jupyter notebook is a fusion of two very fundamental technologies
    * Markdown: A simple notation convention to create formated text using a plain text editor
    * Python: Our programming language
 * In short jupiter notebook is a simple file with the ending .ipynb
 * Visual Studio Code (or in Jupyterlab, wich is another tool work with Jupyter notebooks) help you make these files interactive
 * Inside these file we can create blocks
    * Markdown blocks to wirte text
    * Python blocks to write code
 * Each python block is followed by an output block where we see the results of the python code.
 %% Cell type:markdown id: tags:
 ## Let's Create our First Notebook
 <img src="images/pynb-hello-world.png" class="float-left" />
 You see, it's simple...
 %% Cell type:markdown id: tags:
 ## Here's What a Real Document Could Look Like
 [Example](http://localhost:8888/notebooks/lecture1/example.ipynb#)
 Need more hints?
 * This a good introduction to jupyter notebooks: https://www.dataquest.io/blog/jupyter-notebook-tutorial/
 * This is a good guide to work with jupyter in VSCode: https://code.visualstudio.com/docs/datascience/jupyter-notebooks
 %% Cell type:markdown id: tags:
 ## The most Important Markdown Rules
 | Sign            | Explanation                   | Exampe                                  |
 | --------------- | ----------------------------- | --------------------------------------- |
 | `# Title`       | Heading 1                     | <h1>Heading 1</h1>                      |
 | `## Title`      | Heading 2                     | <h2>Heading 1</h1>                      |
 | `*some text*`   | Italic                        | *This is italic text*                   |
 | `**some text**` | Bold                          | **This is bold text**                   |
 | `* Point`       | Bullet point                  | <ul><li>Point 1</li></ul>               |
 | `1. Item`       | Numberd Item (allways use 1.) | <ol><li>Item 1</li><li>Item 2</li></ol> |
 | `---`           | Horizontal line               |                                         |
 | \`code\`        | Code (mono spcae)             | `code example`                          |
 For further reference go here: [https://markdownguide.org/cheat-sheet/]
 %% Cell type:markdown id: tags:
 # We did it, that's all for today.
 ## *Now let's get our hands dirty!*

--- a/unit-2/.ipynb_checkpoints/02_basics-checkpoint.ipynb
+++ b/unit-2/.ipynb_checkpoints/02_basics-checkpoint.ipynb
--- a/unit-2/02_basics.ipynb
+++ b/unit-2/02_basics.ipynb