TRAIN FOR SUCCESS

A TRAINING COURSE IN THE FIELD OF SOFTWARE DEVELOPMENT

Python for AI applications

The “Python for AI Applications” training is of great importance for engineers in the automotive industry. Python is one of the most widely used programming languages in AI and data science community due to its simplicity and flexibility as well as the wide range of libraries and frameworks it supports.

In this course, you will learn the basics of the Python programming language. You will be familiarised with the basic concepts and structures of Python and learn to write effective and efficient code.

You will also be introduced to the use of Python libraries for AI and data science. These include libraries such as NumPy, Pandas, Matplotlib, Scikit-learn and TensorFlow, which provide a variety of functions for data manipulation, analysis and visualisation as well as machine learning and neural networks.

Another important part of the training is the introduction to neural networks and deep learning. You will learn how to use these powerful techniques to recognise complex patterns in data and create predictive models.

Finally, you will learn about various Python tools to help you write, debug and optimise your code. These include integrated development environments (IDEs) such as PyCharm and Jupyter Notebook as well as version control systems such as Git.

Overall, this course provides a comprehensive introduction to using Python for AI applications and prepares you to use these powerful tools effectively in your work in the automotive industry. It is valuable and essential training for any engineer in the automotive industry.

Target Group

  • Specialists with tasks in the areas of vehicle development, workshops or test benches

Learning Objectives

  • Python programming language
  • Libraries for AI and data science
  • Neural networks and deep learning
  • Python tools

Training Content

  • Introduction to the Python programming language
  • Use of NumPy and Matplotlib
  • Case studies
  • Feedforward Neural Network
  • Supervised Learning

Key Facts

  • Duration: 2 days
  • Number of participants: by arrangement or up to 12 participants
  • Format: Presence, hybrid or online
  • Prerequisites:
    • Basic knowledge of a programming language
    • Installation of Visual Code (free of charge) on the participant’s computer
    • A second computer monitor is recommended in online format
  • Costs: You will receive a detailed offer from us on request
Carolin Jaskolka
Strategic Business Development
+49 173 1707116
carolin.jaskolka@mdynamix.de