Python for Data Science

Price
Net €
VAT €

Price
Price on Request

Duration
3 days

For companies and job seekers:
this course is 100% fundable!

Location

Course Language
English

Training Solutions
Online Live

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Data shapes decisions, products, and business models. Python is considered the key language for modern data analysis and AI-related applications. This training course provides a solid understanding of data-driven work with a clear practical focus.

Key topics

Working with data structures and libraries.
Data analysis, statistics, and visualization.
Fundamentals of machine learning and AI applications.
Efficient processing of large amounts of data.
Clean, traceable code for analysis projects.

Prerequisites
Basic technical understanding and interest in data and analysis.

Target group
Professionals from IT, analysis, science, technology, and related fields with a focus on data, AI, and automation.

Python provides stable access to data science and AI-related methods and creates a solid foundation for analytical work in modern, data-oriented environments.

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Course content

Module overview

Python
Jupyter notebooks
Numpy
Pandas
Data input/output
Excel
CSV
SQL
Conversion of data sets into data frames
Adjustment of specific data with user-defined functions
Handling missing data
Aggregation of data
Matplotlib for customizable charts
Implementation of custom numbers and axes
Seaborn for statistical visualizations
Scatter plots
Distribution charts
Box plot charts

Your training will be 100% funded

Our funding schemes are available exclusively to participants who live or work in Germany. Funding is not available outside Germany.

For career starters, job seekers, career changers, startups, experienced professionals, those looking to advance their careers, specialists, etc.

The QCG program for everyone in the company

Further information

The education voucher for all job seekers

Further information

Frequently asked questions

What is Python for Data Science?

Python for Data Science describes the use of the Python programming language for analyzing, processing, and visualizing data to make informed decisions.

Why is Python particularly popular for data science?

Python is easy to understand, versatile, and offers powerful libraries for data analysis, machine learning, and artificial intelligence.

What tasks can be implemented with Python in data science?

Typical tasks include data preparation, statistical analysis, forecasting, automation, and clear visualization of large amounts of data.

Which Python libraries are important for data science?

Pandas is often used for data analysis, NumPy for calculations, Matplotlib for visualization, and Scikit-learn for machine learning.

Is prior knowledge of Python for Data Science required?

Basic programming skills are helpful but not essential, as Python offers a simple and easy-to-read syntax.

In which areas is Python used for data science?

Areas of application include business, marketing, research, IT, finance, healthcare, and many data-driven industries.

What advantages does Python for Data Science offer in everyday working life?

Python supports efficient data analysis, better decision-making, process automation, and getting started with AI projects.

Do you have any further questions? Please contact us.

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