Introduction in Data Science with Python (PYE)

Training course goals:

The aim of this course is to learn the basic concepts of Data Analysis using the programming language Python. The participants receive an overview and a systematic introduction to the most important software packages for Python in the Data Science environment.

Target group:

This course addresses all users who are interested in using Python for Data Analysis.

Course contents:

The software packages which expand Python to a comprehensive Data Analysis plattform are systematically introduced. The basic concepts of data structures and data management are taught using the Python package Pandas. The creation of basic and advanced plotting capabilities using the plotting packages Matplotlib and Seaborn are presented. Concepts of basic statistical techniques and Data Mining are presented using the Scikit-Learn package.

The subjects:

  • Overview: Python Basics
  • Overview to the Python software packages in the Data Science environment
  • Data import and export
  • Data management and data cleaning
  • Creation of basic plots (histogram, line plot, scatter plot, box plot)
  • Customization of plots and combination of plots
  • Basic analytical techniques (regression, clustering, classification)

This course consists of an explanation of the topics, as well as the presentation of different examples. Multiple training examples are used as exercises to help further in understanding all the topics.

Requirements:

To take the full advantage of the training, participants should be familiar with the basic concepts of programming languages (data types, variables, functions) and should have basic knowledge in statistical concepts.

Supplementary courses:

Further courses in the Python environment are currently under development. Please contact us if you are especially interested in a specific topic.

Furthermore, we offer a series if methodological courses, which cover different software independent topics, for example methodological courses as “Efficient Data Management” (EDM), “Big Data Analytics” (BDA), “Decision Trees” (TRM), as well as “Methods of Statistical Data Mining” (MDM) and “Data Mining in Practice” (PDM).

Duration: 2 Days             Time: 9:30 - 17:00 h            Price: EUR 1.040,- (plus VAT) per participant

 

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