Masterclasses

/Masterclasses
Masterclasses2019-06-05T15:47:54+00:00

Three masterclasses are provided by VBTI that can be ordered with the following options:

  • 1-day in-company masterclass
  • 1-day in-company masterclass + 1-day AI ideation

Participants receive a paper handout and will carry out exercises using Jupyter notebooks. Contact us for more information or ordering a masterclass.

The ‘Introduction Deep Learning’ masterclass is currently also provided as ‘open class’ via the High Tech Institute.

Introduction to Deep Learning

Dive into deep learning with this practical masterclass

  • Get an overview of deep learning techniques in one day;
  • Get up-to-speed with deep learning.

This 1-day masterclass brings you up to speed in deep learning, one of the fastest developing fields in artificial intelligence. You will get an overview of the latest deep learning trends and techniques from both lectures and exercises.

The one day masterclass ‘Introduction to Deep Learning’ is intended for software and hardware engineers, application and process engineers, system architects and managers with technical background.

Prerequisites are basic mathematics skills and basic (python) programming skills.

Objective

After this 1-day masterclass the participants will have an understanding of the latest artificial intelligence / deep learning techniques. More specifically, they will:

  • Understand the latest artificial intelligence / deep learning trends;
  • Understand the intuition behind artificial neural networks;
  • Understand the intuition behind convolutional neural networks;
  • Understand the intuition behind recurrent neural networks;
  • Understand the intuition behind reinforcement Learning;
  • Get an overview of deep learning software tools;
  • Carry out deep learning exercises.
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Introduction to Machine Learning

Analyse data and train models with this practical masterclass

  • Get an overview of machine learning techniques in one day;
  • Get familiar with standard machine learning Python tools.

This 1-day masterclass brings you up to speed in machine learning. You will get an overview of machine learning trends and techniques from both lectures and exercises.

The one day masterclass ‘Introduction to Machine Learning’ is intended for software and hardware engineers, application and process engineers, financial experts, system architects and managers with technical background.

Prerequisites are basic mathematics skills and basic (python) programming skills.

Objective

After this 1-day masterclass the participants will have an understanding of machine learning techniques. More specifically, they will:

  • Understand the machine learning model building workflow;
  • Understand different data types;
  • Understand why and how to preprocess data;
  • Understand feature engineering;
  • Understand the three challenges of Big Data;
  • Understand difference between supervised and unsupervised learning;
  • Get an overview of different regression techniques;
  • Get an overview of different classification techniques;
  • Get an overview of machine learning software tools;
  • Carry out machine learning exercises.
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Deep Reinforcement Learning

Build self-learning algorithms that optimize processes and problems

  • Get an overview of reinforcement learning (RL) techniques in one day;
  • Get familiar the latest Deep RL techniques as used by DeepMind.

This 1-day masterclass brings you up to speed in Deep Reinforcement Learning. Deep Reinforcement Learning is a new AI techniques that learns to optimize processes and problems. You will get an overview of reinforcement learning trends and techniques from both lectures and exercises.

The one day masterclass ‘Reinforcement Learning’ is intended for software and hardware engineers, game developers, robot engineers, application and process engineers, control engineers and system architects.

Prerequisites are mathematics skills and basic (python) programming skills.

Objective

After this 1-day masterclass the participants will have an understanding of reinforcement learning techniques. More specifically, they will:

  • Understand the reinforcement learning framework;
  • Understand solving the RL by dynamic programming;
  • Understand solving the RL by Monte Carlo simulation;
  • Understand solving the RL by Temporal Difference learning;
  • Understand difference between tabular and function approximation approach;
  • Understand Deep Reinforcement Learning, such as DQN, DDQN, BDQN;
  • Understand replay memory techniques;
  • Carry out reinforcement learning exercises, including training an algorithm to play Atari games.
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