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Deep learning is one of the hottest trend in data analysis. It has pushed the boundaries in data analytics and AI across a wide range of domains. These include object classification in vision systems, natural language processing such as seamless translation and network intrusion detection systems. Deep neural network powered the AlphaGo system.

Increasingly, it is not only leading players such as Google and Facebook, but also small and medium sized companies that are successfully applying deep learning techniques to solve commercially relevant problems in a broad variety of areas from DNA sequencing, CRM and loan risk estimation.

Our training courses are focused on small group sessions with lots of hands-on practical learning. We will give you a detailed insight into deep learning, introducing you to the basics as well as to the latest tools and methods in this emerging field.

What you will learn

By completing the course, you will be able to set up and use basic deep learning techniques. You will learn how to use deep convolutional neural networks and recurrent neural networks for image, text, and time series analysis tasks. You will also become acquainted with advanced tools and become familiar with using appropriate computational resources to train and apply deep learning models.

The course will also teach you the theoretical foundations of deep neural networks, which will provide you with the understanding necessary for adapting and successfully applying deep learning in your own applications.

Course Content

Deep learning refers to machine learning algorithms that process data in multiple stages, each stage working on a different representation of the data. These representations are learned and enable data to be analyzed at different levels of abstraction.

Core learnings

• Thorough introduction to the basics of neural networks including how to train them (e.g. back propagation)
• Introduction to convolutional neural networks
• Introduction to recurrent neural networks, for example long short-term memory networks (LSTMs) and gated recurrent units (GRUs), for time series modelling and predicting
• Training and applying convolutional and recurrent neural networks for text- and image analysis
• Utilizing data augmentation and other preprocessing steps to further improve the generalization
• Introduction to generative adversarial networks (GANs)
• Using modern software tools for deep learning, in particular TensorFlow (used by DeepMind, Google Brain, Ebay, Twitter, Qualcomm, SAP etc.)
• Application examples presented by experts with first-hand experience in applying deep learning in scientific and commercial applications
• Exploiting appropriate hardware systems to speed up the computeintensive process of generating complex deep learning models
• Deep reinforcement learning i.e., how deep neural networks can learn to interact with an environment
• Introduction to Restricted Boltzmann Machines and Deep Belief Networks, which are deep generative models

All the techniques covered can easily be implemented with Python, which will be the programming language used throughout the course.

Participants

The course is for professionals who need state-ofthe art skills in deep learning analytics. Participants should:

• Be acquainted with data analysis i.e. hold a relevant bachelor degree or equivalent and/or have several years of data analysis experience
• Have elementary programming knowledge
• Have an interest in programming (the programming on the course will mostly be done in Python, which you can easily pick up using the course material)
• Have a background in statistics and/or conventional data analysis (it is assumed that participants have elementary knowledge of linear algebra and calculus and can recall what a derivative and a scalar product is)
• You will have the opportunity of refreshing your linear algebra and calculus as necessary using the course material, which will be sent out to participants before the start of the course.

Our training sessions run regularly in Dublin and Cork. To find out more about our training course timetable for 2019 or to arrange a custom in-house training event tailored to your specific company needs please contact us