PowerPackage Python

This PowerPackage combines the content of the courses Python for Data Science - Data Analysis and Insight Machine Learning and Machine Learning Workshop - Hands-on Data Analysis with Python in one event.

The programming language Python offers an ideal platform for data scientists with an extensive landscape of libraries for data processing, evaluation and visualization as well as the architecture of machine learning models. The participants of the training quickly learn the most important basics of the Python programming language and work through the basics of handling data (including import, processing, analysis and presentation) in interactive exercises. The workshop also provides an initial insight into the topic of machine learning and works on an initial example based on a classification.

Data science and machine learning are no exception: gray theory cannot replace practical experience. Data handling and analysis are best learned in their application. By making mistakes and retrospectively deriving insights from them, you consolidate your wealth of experience and knowledge. In this course, participants will use a case study to cover all aspects of data analysis and the development of machine learning models. Starting with data collection, processing and cleansing the data, through to simple statistical models, hypotheses and finally the training and validation of machine learning algorithms, the course covers all aspects of the work of a data scientist.

Part 1

• Basics of the Python programming language
• Efficient numerical calculations (with numpy)
• Processing and explorative analysis of data (with pandas)
• Visualization (e.g. matplotlib, plotly)
• Overview of machine learning concepts (including algorithmic and statistical basics, learning scenarios, metrics, evaluation)
• Machine learning pipeline using the example of classification (with scikit-learn)
• Interactive material and continuous interactive exercises (with Jupyter notebooks)

Part 2

Repetition

• Working interactively with Jupyter Notebooks
• Python (basics & libraries: numpy, pandas, matplotlib, scikit-learn)
• Machine Learning

Presentation of the case study

• Description of the problem
• Joint brainstorming on the procedure
• Presentation of a minimal prototype

Group work of the participants

• Regular Q&A rounds
• Individual assistance

Presentation of the results

The detailed digital documentation package, consisting of an e-book and PDF, is included in the price of the course.

The course is aimed at users who are looking for an introduction to the topic of data analysis and its implementation with Python and who want to practice handling real data and implementing machine learning solutions using a case study.

Participants in this workshop should have an interest in working with data and statistical methods and be familiar with the basics of programming. Basic knowledge of the Python programming language is an advantage.

Please also see our overview of Python training and the blog articles Why you should learn Python! and Analyzing log files with Python - How to avoid layer 2 loops.