1. Programming for Data Science and Artificial Intelligence

This script accompanies the course „Programming for Data Science and Artificial Intelligence“ in the DAISY program at Hochschule Düsseldorf (HSD). It is continuously updated and expanded to meet the evolving demands and developments in these dynamic fields.

1.1. Why is Programming Important for Data Science and Artificial Intelligence?

Computers have the remarkable ability to perform millions of calculations per second and store vast amounts of data. This computational power is essential in the fields of Data Science and Artificial Intelligence (AI). Of course, numerous software solutions are already available to handle many of these tasks. However, specific problems often require individual solutions that existing programs cannot provide. This is why we need to create our own programs, i.e., we need to program.

Although there are many definitions of programming, we can simplify it as follows: Programming means transforming tasks or calculations into a form that a computer can execute. In most cases, this involves writing program code that contains the instructions for the computer.

What makes programming unique is its exact and precise nature of communication. While humans often rely on prior knowledge and context in conversation, computers do not. Human language, known as natural language, is often ambiguous. A well-known example is the sentence: „I saw the man with the telescope.“ This sentence has at least two interpretations: Either I saw a man holding a telescope, or I saw a man through a telescope. Humans often understand the correct meaning from the context – computers, however, do not.

To avoid such ambiguity, we use formal languages, particularly programming languages.

In summary:

A programming language must be absolutely precise and unambiguous because the computer cannot recognize context or interpret meaning. It is used to define data structures and algorithms that a computer should execute.

In this course, we will learn programming with Python. But why Python?

1.2. Python

Python is an interpreted programming language with dynamic typing. This means that code written in Python does not need to be compiled before it is executed. Instead, the code is directly interpreted and executed by an interpreter. This enables rapid and flexible development, which is particularly advantageous in the fields of Data Science and AI, where frequent adjustments and iterations are necessary. For this reason, Python is often referred to as a scripting language.

1.2.1. Types of Programming Languages

Python has emerged as the most popular programming language in the fields of Data Science and Artificial Intelligence in recent years. This offers several key advantages:

1. Large User Base: A vast number of users employ Python for similar purposes. As a result, there are many online forums, tutorials, and other resources available for assistance.

2. Extensive Libraries: The large community continuously develops the language and provides numerous libraries that can be used for tasks in Data Science and AI.

3. Adaptability: Python is regularly updated to accommodate new technological developments and hardware requirements.

4. Code Readability: Python is often praised for its comparatively high readability. This does not necessarily mean that the code is immediately understandable for beginners but rather that it is clearer and more structured compared to other languages. This characteristic is particularly advantageous for teamwork or when further developing projects.