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Introduction to Python for Data Science

Course 2021-05

Online Workshop

Dates: 3, 4, 5, 8 + 9  February 2021,  9:00 -12:00 each day + 3 February 2021, 14:00-17:00

Trainer: Andreas Wygrabek, Kassel

Working place with laptop, papers and pens.

Data is the oil of the 21st century and programming and analytical skills are at the core in many professions. Focusing on the 3 areas of programming, data management and machine learning, this course teaches the basics of Python in the context of data science applications.
From the installation, the essential object types and the programming basics to the creation and management of projects, the participants in this training will get initially all the prerequisites to write applications in Python. In practical examples and with the help of example data the participants will learn the most important techniques in the field of data management. The final program item of the course is the analysis and forecasting of data using machine learning techniques. First, the topic machine learning is theoretically introduced and then applied directly with Python in two scenarios based on a sample data set. The scenarios solve a classification and a regression problem.
The course focuses on the popular Python libraries numpy and pandas for data storage as well as scikit-learn for analysing data using machine learning techniques.

The training addresses people who want to take their first steps in Python to use the language for data analysis. The course is an introductory event. No prior knowledge is required.

  • Overview of data analytics with python
  • The concept and philosophy of Python
  • Python data structures and their properties
  • Functions, control structures and classes in Python
  • Data management with pandas
  • Introduction of machine learning processes
  • Machine Learning and forecasting with Python and scikit-Learn
Prerequisites for your particiption: no previous knowledge of Python, but your PC/notebook must have the following software installed:
  • Python (Anaconda-Distribution) in current Version (the development environments 'Jupyter Notebooks' and 'Spyder' should be set up; Python should be entered in the environment variables of the operating system – this can already be done during the installation)
  • PyCharm in current version (Community-Version)

The online seminar is fully booked. Registration is no longer possible.

About the Trainer

Andreas Wygrabek is a freelance data science expert and experienced trainer in programming and statistics with a career background in an IT consultancy. With his project data-science-architect he is offering data science services for industry and academic institutions. In his projects he is revealing insights from data through the use of modern algorithms and visualization techniques. The toolset he uses covers the most popular programming languages in the field of data science – R and Python.