Course Code

aiauto

Duration

14 hours (usually 2 days including breaks)

Requirements

The participants must have programming experience (any language) and engineering background, but are not required to write any code during the course.

Overview

This course covers AI (emphasizing Machine Learning and Deep Learning) in Automotive Industry. It helps to determine which technology can be (potentially) used in multiple situation in a car: from simple automation, image recognition to autonomous decision making.

Course Outline

Current state of the technology

What is used
What may be potentially used

Rules based AI

Simplifying decision

Machine Learning

Classification
Clustering
Neural Networks
Types of Neural Networks
Presentation of working examples and discussion

Deep Learning

Basic vocabulary
When to use Deep Learning, when not to
Estimating computational resources and cost
Very short theoretical background to Deep Neural Networks

Deep Learning in practice (mainly using TensorFlow)

Preparing Data
Choosing loss function
Choosing appropriate type on neural network
Accuracy vs speed and resources
Training neural network
Measuring efficiency and error

Sample usage

Anomaly detection
Image recognition
ADAS

Testimonials

★★★★★

It was very interactive and more relaxed and informal than expected. We covered lots of topics in the time and the trainer was always receptive to talking more in detail or more generally about the topics and how they were related. I feel the training has given me the tools to continue learning as opposed to it being a one off session where learning stops once you've finished which is very important given the scale and complexity of the topic.

Jonathan Blease

Course:Artificial Neural Networks, Machine Learning, Deep Thinking

The topic is very interesting.

Wojciech Baranowski

Course:Introduction to Deep Learning

Trainers theoretical knowledge and willingness to solve the problems with the participants after the training.

Grzegorz Mianowski

Course:Introduction to Deep Learning

Topic. Very interesting!.

Piotr

Course:Introduction to Deep Learning

Exercises after each topic were really helpful, despite there were too complicated at the end. In general, the presented material was very interesting and involving! Exercises with image recognition were great.

Dolby Poland Sp. z o.o.

Course:Introduction to Deep Learning

I think that if training would be done in polish it would allow the trainer to share his knowledge more efficient.

Radek

Course:Introduction to Deep Learning

The global overview of deep learning.

Bruno Charbonnier

Course:Advanced Deep Learning

The exercises are sufficiently practical and do not need high knowledge in Python to be done.

Alexandre GIRARD

Course:Advanced Deep Learning

Doing exercises on real examples using Eras. Italy totally understood our expectations about this training.

Paul Kassis

Course:Advanced Deep Learning

We have gotten a lot more insight in to the subject matter. Some nice discussion were made with some real subjects within our company.

Sebastiaan Holman

Course:Machine Learning and Deep Learning

The training provided the right foundation that allows us to further to expand on, by showing how theory and practice go hand in hand. It actually got me more interested in the subject than I was before.

Jean-Paul van Tillo

Course:Machine Learning and Deep Learning

I really enjoyed the coverage and depth of topics.

Anirban Basu

Course:Machine Learning and Deep Learning

The deep knowledge of the trainer about the topic.

Sebastian Görg

Course:Introduction to Deep Learning

In-depth coverage of machine learning topics, particularly neural networks. Demystified a lot of the topic.

Sacha Nandlall

Course:Python for Advanced Machine Learning

way of conducting and example given by the trainer