DATA SCIENCE BASICS
DATA SCIENCE BASICS
Data analysis with Python
Data plays an increasingly important role in our digitized world and forms the basis of political and economic decisions. The term big data or data science summarizes technologies that deal with the analysis and evaluation of very large amounts of data.
The application of data science leads to the optimization of processes and structures. Trends can be identified at an early stage and forecasts can be made with increasing accuracy. Python is one of the most widely used programming languages in the fields of data science and machine learning and has extensive modules for processing large amounts of data.
The application of data science leads to the optimisation of processes and structures. Trends can be identified at an early stage and forecasts can be created with increasing accuracy. Python is one of the most widely used programming languages in the fields of data science and machine learning and has extensive modules for processing large volumes of data.
Course content
Learning goal
Pace of learning
Access
prerequisites
Certificate
Target group
We'll start with a quick review of Python basics before we get into data analysis with Python. Basic statistical knowledge is also refreshed in the first module. The main modules of this course are pandas and Matplotlib. They can be used to process, evaluate and visualize large amounts of data. We work with real external data sets, which we import and work along the data pipeline: processing, analysis and visualization.
By the end of this course you will have a very good overview of how big data works. You will have learned how large data sets can be imported and processed from various external sources. You know the modules in Python with which large amounts of data can be analyzed and visualized and be able to apply them.
This course has a medium learning pace.
Programming knowledge in Python is required, we recommend attending the Python Basics course. Knowledge of statistical evaluations is an advantage.
At the end of the course you will receive a certificate of participation in which the scope and the high practical content of the online training will be listed.
Specialists and executives who have to work with large amounts of data in a digitized environment and make data-based decisions.
This is how the online training is structured
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This interactive live webinar is divided into four modules (each 2 hours live training + 1 hour self-learning phase).
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In a small group of up to eight people, you will learn under the guidance of an experienced trainer in a video conference.
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You solve tasks in individual work, but also in a team in break-out sessions.
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At the end of a module there is homework that you work on in the self-study phase.
Course content
Refresher on Python Basics
Introduction to Data Science and the use of Python for data analysis
Statistics Basics
Introduction to the Python module Pandas
Reading and evaluating data
Data visualisation with Matplotlib
Interactive live coding
Self-learning phase in each module
In the self-learning phase, you consolidate what you have learned in live training. Your trainer gives you homework every day, which you can solve at your own leisure. If you have any questions or get stuck, you can contact your trainer or other course participants in the Slack workspace.