Introduction to Data Science with Python
Course Objective
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. However, the first steps in coding can be intimidating and discouraging—especially if you have never worked with a programming language before. 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, visualizing data, and applying 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.
Course Description
This course aims at beginners. Hence, we will cover Python’s programming fundamentals, such as variables, loops, and logic statements, before we dive into Data Science.
You will learn:
- Syntax and basics of Python and how to use Jupyter Notebooks as a coding environment
- Data analysis, data wrangling, and data visualization using numpy, pandas and matplotlib
- Introduction on how to use simple statistical models in Python with scikit-learn
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 you need 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.)
Course Material
You can find the lecture slides here.
The Google Colab notebook with the exercises is here.
Happy coding!