Professional training – Python Programming

Numerical Computing with NumPy

Numerical Computing with NumPy in 6 focused hours: ndarray and dtypes, Broadcasting and Vectorization – practical, with exercises and templates for your daily work.

Duration
6 hours, one session
Level
Intermediate
Format
Online or on-site
Language
German or English
Certificate
Certificate of attendance

Overview

“Numerical Computing with NumPy” is a compact live course in the field of Python Programming. It centres on ndarray and dtypes, Broadcasting and Vectorization – explained with realistic examples and deepened in exercises you can transfer straight to your daily work.

Python is the default language for automation, data analysis, web applications and scripting in daily operations. In our Python courses, teams learn to write clean, maintainable code, automate recurring tasks and choose libraries deliberately. Every course is a one-day workshop: short technical input followed by exercises based on tasks from your own work. Numerical Computing with NumPy is aimed at developers, domain specialists and administrators who want to use Python productively. You work in a prepared development environment and take home runnable examples, templates and a checklist for applying the content in your projects.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Focus areas of the course

ndarray and dtypesBroadcastingVectorizationLinear algebra with numpy.linalgRandom numbers and simulationPerformance comparison with loops

Who is this course for?

  • Developers and software engineers
  • Data analysts and domain specialists who need automation
  • Administrators and DevOps engineers
  • Engineers and scientists

What you will be able to do

  • You know the key topics of Numerical Computing with NumPy – ndarray and dtypes, Broadcasting, Vectorization, Linear algebra with numpy.linalg, Random numbers and simulation and Performance comparison with loops – and can apply them in practice.
  • You apply Numerical Computing with NumPy confidently in your own Python projects.
  • You write readable, tested and maintainable code.
  • You choose suitable libraries and tools for your task.
  • You transfer the exercises to your daily work and solve your own cases independently.

Course outline

Module 1 Getting started and environment for Numerical Computing with NumPy
  • Where Numerical Computing with NumPy fits in the Python ecosystem
  • Interpreter, virtual environments and editor setup
  • Project layout and dependency management
  • Reading and running the sample projects
Module 2 Focus areas: Numerical Computing with NumPy
  • ndarray and dtypes
  • Broadcasting
  • Vectorization
  • Linear algebra with numpy.linalg
  • Random numbers and simulation
  • Performance comparison with loops
Module 3 Core concepts of Numerical Computing with NumPy
  • Key language features and libraries for the topic
  • Typical patterns and idioms from real projects
  • Common pitfalls and how to avoid them
  • Using the documentation and standard library effectively
Module 4 Hands-on exercises with Numerical Computing with NumPy
  • Guided exercises on realistic tasks
  • Building your own scripts and modules step by step
  • Troubleshooting with the debugger and logging
  • Group code review of the results
Module 5 Quality and transfer to your projects
  • Tests, linting and formatting as routine
  • Maintainability, readability and structure
  • Fitting into existing pipelines and team processes
  • Next learning steps and further resources
Module 6 Transfer to your daily work
  • Exercise based on a realistic case
  • Typical mistakes and how to avoid them
  • Checklist and templates to take away
  • Open questions, outlook and resources for further learning

Prerequisites

Depending on the level, general computer skills or first programming experience are enough. Advanced courses benefit from solid Python basics. Basic knowledge of the topic is helpful.

Technical requirements

Your own laptop with internet access; Python and the development environment are provided in advance as a setup guide or a prepared environment.

Dates & locations

For every location we suggest a date roughly four weeks ahead. Your preferred date is always possible.

  • Munich Tue, 15 December 2026 6 hrs Request
  • Salzburg Mon, 14 December 2026 6 hrs Request
  • Berlin Fri, 11 December 2026 6 hrs Request
  • Augsburg Tue, 15 December 2026 6 hrs Request
  • Hanover Wed, 16 December 2026 6 hrs Request
  • Bremen Thu, 10 December 2026 6 hrs Request
  • Stuttgart Tue, 15 December 2026 6 hrs Request
  • Kaiserslautern Wed, 16 December 2026 6 hrs Request
  • Online Fri, 11 December 2026 6 hrs Request

Frequently asked questions

Who is Numerical Computing with NumPy suitable for?

Numerical Computing with NumPy is designed for professionals who use or need to use Python at work. The prior knowledge that makes sense depends on the course level. If you are unsure, we advise you beforehand and adjust content and pace to your team so that nobody is overwhelmed or under-challenged.

Do we work with our own data and tasks in Numerical Computing with NumPy?

Yes, if you wish. By default we use realistic sample datasets and tasks. For in-house sessions we can include your scripts, data formats or projects, provided you share them in advance. This way, what you learn goes straight into your daily work.

How much does “Numerical Computing with NumPy” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 6 hours of live training with a trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. For every location we suggest a date roughly four weeks ahead. In the request form you can always describe your preferred date or period in free text – we check availability and get back to you within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run the course exclusively for your team.

Can the course be tailored to our team?

Yes. Tailor-made courses cost approx. €4,500 more, depending on the topic and by arrangement. We agree content, examples and exercises with you in advance.

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