Learn to build it in Germany.

New Course: Autonomous and Connected Vehicles

Starting 04 September 2017


    what you get

  • 600+ hours hands-on practice        
  • Employment opportunities in Germany
    and worldwide
  • Advanced Coding in Python & C++  
  • Automotive AI experts as trainers  
  • Communication skills to makeyour use & business case
  • Portfolio Project demonstrating your competence
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Why should I take the course?

Deep Learning and Robotics are key to self-driving cars as well as to connected vehicles. These vehicles are going to change our cities, our lives, and the way we organise mobility. You can become part of this exciting venture by training in Germany, home to brands like Audi, BMW, Mercedes, Porsche, and Volkswagen, as well as large automotive suppliers, startups, and new mobility solutions including freight and public transport. Our intensive 3 month course inducts you into the autonomous and connected vehicle industry. Shape the future by starting your career now.


Duration: 3 Months
Course fee:  €10,000


This is a demanding course and it is vital that you have prepared. Qualified applicants will be offered an interview. Please consider the following points.

1. Domain knowledge: What do you know about deep learning, robotics, the automotive industry, and new mobility solutions? You don't need to be great, otherwise you would not need te course. But you should have been following blogs and twitter at the very least to get a gist of what is going on in this field.

2. Coding skills: What have you done in Python or C++? You don't need to know both.

3. Track record: In education and work, which is the most impressive project you have completed?


Expertise we have developed

We co-developed
Curriculum  with
Audi Electronic Ventures

For AUDI engineers, we provide Training at
Audi Academy in Ingolstadt


 Key topics include


Introduction to Python  •
Unsupervised Learning •
 Mathematical Refresher
Data Preparation & Analysis •
Supervised Learning •

    (Deep) Neural Networks  
    • Optimization & Regularization
    • Decision Trees
    • Reinforcement Learning
    • Visualisation

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    Berlin, 14 July 2017

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