This repository contains all materials for the course Introduction to Data Science with Python, offered for GRADE Brain and other GRADE Centers at Goethe University. Additionally, it serves the course website for students, which you can access here.
Data analysis plays a critical role in many academic disciplines, and the Python programming language has become one of the standard tools within the Data Science community. This course will introduce programming with Python and how to use it for data analysis. After successfully completing this course, you will be able to understand the fundamentals of the Python programming language. This skill set includes basic data analysis by data wrangling, data visualization, and implementing simple statistical models in Python.
Our goal is to show you the scope of possibilities within Python and leave you with the impression that you can confidently implement your own empirical projects in Python.
This course aims at Python beginners. Hence, we will cover the fundamentals of programming and Python, such as variables, loops, and logic statements, before we dive into the topic of Data Science. This course will not cover deeper statistical or theoretical concepts as we focus on applied coding.
This course introduces:
- Syntax and basics of Python
- How to use Notebooks as a development environment
- Data analysis, data wrangling, and data visualization using numpy, pandas and matplotlib
- Introduction to implementing simple statistical models in Python with scikit-learn
The course will alternate between short introductions to a concept or method and small do-it-yourself coding exercises. This course will not cover more profound statistical or theoretical concepts, as the focus will be applied coding.
No prior coding experience is needed. This course is a beginner-friendly course.
We want you to make your hands dirty — that means we want you to code! Just following along fancy slides won’t magically transfer the skill of coding to you. But you actively engaging with the course content in your development environment will more likely do just that. That’s why we need you to prepare accordingly: Please ensure that you have access to Google Colab before the course. We will use Google Colab for the coding parts, such that we can use Python without (sometimes time-consuming) pre-configuration or installation on your machine. To use Google colab, you need a Google account (same account which is used for Gmail, YouTube, etc.) If you have any questions, please reach out to one of us through the e-mail addresses indicated on the course website.
- Thilo Kraft, Ph.D. Student in Quantitative Marketing
- Jan Bischoff, Business and Economics Student, R/Python Teacher and Course Designer at TechAcademy e.V.