- Introduction Deep Learning;
- Artificial Neural Networks;
- Software & Hardware frameworks;
- Convolutional Neural Networks;
- Recurrent Neural Networks;
- Reinforcement Learning.
Total: 8h + 1h lunch
Get an introduction with this 1-day masterclass to one of the fastest developing fields in Artificial Intelligence: Deep Learning. Deep Learning technology matured rapidly during the last 7 years and is currently applied to many existing and new applications, including self-driving cars, drones, intelligence machines, robotics, speech recognition systems, predictive maintenance, smart camera’s and more. The technology is so powerful that it beat world’s number one in ancient game of Go.
During this course you get an overview of the latest Deep Learning trends and techniques. The course starts with explaining general concepts and trends. Why does Deep Learning get so much attention now? Is it a hype? Next, four major Deep Learning technologies are discussed:
Artificial Neural Networks: The basic model behind many deep learning techniques.
Convolutional Neural Networks: Neural networks specialized to process images.
Recurrent Neural Networks: Neural networks optimized to process time-series data.
Reinforcement Learning – Algorithm to learn optimal sequence of actions
During each chapter participants will gain deeper insights by doing exercises using a Jupyter/python environment. Exercises include o.a. training a convolutional neural network to detect objects and training a reinforcement learning agent to learn to drive a taxi.
After this 1-day masterclass you will have an understanding of the latest Artificial Intelligence / Deep Learning techniques. More specifically, you will:
Total: 8h + 1h lunch
Lectures & exercises (Jupyter notebooks, python).
After attending you will receive a High Tech Institute certificate.
‘Thorough, in-depth and also a good practical part.’
‘Most important items I’ve learned: General overview with do’s, don’ts and comparisons.’
* Prices are subject to change. Price correction will be applied at the end of the year.