Deep learning is an emerging Artificial Intelligence technology within the industry that enables systems to learn and improve themselves based on data. These features make this technology promising for the industry and the number of application areas is rapidly increasing. Wondering how to apply deep learning in your company? The Advanced deep learning: foundation course introduces you to the latest techniques and application areas and teaches you how to work with tools and applications.
- Get an clear overview of deep learning theory and tools
- Learn about applications and how to deploy them
- Develop your own algorithms
About the course Advanced deep learning: foundation
This course provides engineers, programmers and researchers with an in-depth insight and understanding of deep learning. You will gain an overview of deep learning theory and tools and learn about various applications.
De deep learning cursus bestaat uit vier delen:
- Introduction deep learning
- Artificial Neural Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
For each section, you will receive Python code assignments and projects in the form of Jupyter notebooks. You will learn to develop many of the algorithms yourself so that you have the technical skills to start your own deep learning project.
Specializing in computer vision
After taking this course, you can further specialize in areas such as computer vision. During the course Advanced deep learning: computer vision, you will learn to develop advanced algorithms for applications such as: object detection, image segmentation and generative models. You will also learn to put these applications into practice, for example within industrial or agricultural environments.
Study Load
During the course, assignments will be provided for you to work on at home. For each course day you should take into account +/- 8 hours of 'homework'.
Certificate of Participation
If you complete the course, you will receive a Certificate of Participation.
Program
Day 1: introduction deep learning
- History of Artificial Intelligence
- Overview of deep learning technology
- Introduction of tools like Python, NumPy, Pandas, Matplotlib and Jupyter notebooks.
Day 2: Artificial Neural Networks
Neural networks often form the basis of deep learning algorithms. The following topics will be covered during this class day:
- (multi-layer) perceptrons
- Gradient descent
- RMSProp
- AdaGrad
- ADAM
- TensorFlow
- Keras
- Machine learning training flow
Day 3: Convolutional Neural Networks
Neural networks optimized for computer applications are called Convolutional Neural Networks (CNNs). During this class day, the basics of CNNs will be explained and the following algorithms, among others, will be discussed: AlexNet
- ResNet
- GoogleNet
- MobileNet
Day 4: Recurrent Neural Networks
Neural networks optimized for time series data are called Recurrent Neural Networks (RNNs). Several techniques for time series classification will be discussed during this class day, including:
- LSTMs
- WaveNet
- Backpropagation through time
Your teacher
Dr. Ir. Albert van Breemen
Dr. Ir. Albert van Breemen studied electrical engineering at the University of Twente and received his PhD in the field of intelligent software systems in 2001. He then worked for 8 years at Philips Research within the Ambient Intelligence program on, among other things, Social Robotics. With the project 'iCat user-interface robot' Albert received the Time Magazine Best Invention award in 2005, and in 2007 the New Technology Foundation (NTF) Award on Entertainment Systems and Robots. Albert then worked for over 10 years as Senior New Business Development Manager at ASML. He researched opportunities for ASML in the application of new technologies, including artificial intelligence. He combined his knowledge for technology and sense for value creation to form his company VBTI in 2019.
With his company he focuses on intelligent automation (sensor-data driven applications): AI applied in machines so that customers from High Tech Manufacturing, Mechanical Engineering and Agriculture, among others, can realize until recently impossible solutions and functionalities in very challenging environments. Think of recognizing leaf nodes in cucumber cultivation or harvesting asparagus. The variation of both the plant and the background are pre-eminent challenges where AI over traditional vision techniques offers a solution.
Place, dates and prices - Open registrations
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Mikrocentrum uses all-inclusive rates. All mentioned rates are exclusive of VAT and include course materials and package costs.
Members of the Mikrocentrum High Tech Platform get a 10% discount.
Discover the possibilities to organize this course incompany
If you want to train several employees in your company, it is more interesting and cheaper to organize a course at your location. Good coordination with your company-specific situation and the deployment of highly experienced lecturers who have earned their spurs in practice is essential here. Mikrocentrum is CEDEO-recognized and guarantees the best quality.
Our training manager is happy to think along with you!
Are you interested in an incompany process? Our Training manager Wouter Lintsen will be happy to visit you without obligation.
