Events Outlook

We are pleased to announce the following forthcoming workshops. Details of each workshop will be posted here in due course.

Current Event

Introduction to Machine Learning
This course aims to provide a practical and comprehensive guide to modern machine learning techniques. It provides the delegates a detailed understanding of the fundamental concepts of Machine Learning and its application to data science. Delegates will study important concepts in learning, gain knowledge on both classical and some of the advanced machine learning techniques, be able to synthesise solutions using machine learning paradigm, be provided practical experience with machine learning problems, and understand the inner working of machine learning algorithms. The course is delivered by experienced academics who have over 20 years of combined experience in this field.
Dates: 14 – 15 May 2018.
Two-day workshop; lectures and hands-on lab sessions.
Early registration deadline: 30 April 2018.
Late registration deadline: 7 May 2018.
Follow this link to register for this event. Places are limited to ensure close interaction at hands-on lab sessions.

 

Future Event

Deep Learning Workshop
Recent advances in Deep Learning, more specif- ically Deep Neural Networks, have shown great successes in the fields of speech recognition, autonomous system, computer vision, and health informatics to name a few. This course provides a comprehensive overview of state-of-the-art deep learning techniques, including convolutional neural network and recurrent neural network, and their real world applications, such as natural language processing, speech analysis, and object recognition. Lectures are supported by lab sessions to allow both theoretical understanding and experience in practical implementation. A number of demonstrations with source code in Python will be provided to delegates.
Dates: TBA.
Two-day workshop; lectures and hands-on lab sessions.
Early registration deadline: TBA.
Late registration deadline: TBA.

 

Machine Learning Case Studies
Dates: TBA.
Two-day workshop; lectures and hands-on lab sessions.
Early registration deadline: TBA.
Late registration deadline: TBA.

 

Introduction to Data Mining
Data mining is the computational process that transforms raw data into useful information and high level understanding. It builds upon a host of techniques from statistical analysis, information processing, and machine learning. This course provides an opportunity to learn both practical skills and fundamental concepts in order to carry out pattern discovery from structured and unstructured datasets, and to process data for data clustering, information extraction, information indexing, outlier detection, and knowledge discovery. Lab sessions are intertwined with lectures to provide practical experiences with data mining on real world problems.
Dates: TBA.
Two-day workshop; lectures and hands-on lab sessions.
Early registration deadline: TBA.
Late registration deadline: TBA.

 

Data Analytics and Visualisation
Dates: TBA.
Two-day workshop; lectures and hands-on lab sessions.
Early registration deadline: TBA.
Late registration deadline: TBA.

 

 

 


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