RAIL KNUST organizes a 5-Day Practical Neural Network and Deep Learning Short Course for Everyone

The Responsible Artificial Intelligence Lab (RAIL) at the Kwame Nkrumah University of Science and Technology organized a five-day workshop on practical neural networks and deep learning from 5th to 9th December 2022. 

In attendance were twenty-five (25) participants from diverse fields of study: economics, statistics, graphic design, engineering, and climate sciences. The short course was moderated by Dr. Eric Tutu Tchao, RAIL Partnership Coordinator, and facilitated by Dr. Henry Nunoo Mensah, RAIL Programmes Coordinator. 

Participants were introduced to AI, Fundamentals of Machine Learning, Machine Learning with Regression, Neural Networks and Deep Learning, Commercialization of AI Solutions, and Responsible use of Artificial Intelligence.

In his opening remarks, the Principal Investigator (PI) and Scientific Director, Prof. Jerry John Kponyo, indicated that the short course is meant to arouse participants’ desire and knowledge in AI and to bring together unique experts and practitioners in developing AI solutions to drive the African economy. “And so, we are starting with this, but join our community, join our programs and become an active member as far as RAIL is concerned. I want to open the workshop and say let us create knowledge together,” he intimated. 

The workshop kicked off with a brief introduction to the Python programing language and an introduction to Artificial Intelligence. This was an eye-opener for participants with no knowledge of the Python programing language and those previewed to extensive knowledge of artificial intelligence. There were lectures on python variables and strings, concatenation in python, and the general basics of learning the language. The classifications of AI approaches in AI, and the various fields of AI were all discussed. This saw each participant mentioning one field AI is used and how it impacts their daily activities; it was such an engaging moment and a lot of learning experience.

There were practical sessions where the participants were tasked to develop their models, train them, and make predictions with a set of given datasets. This was to get the participants involved to ensure easy understanding and reinforce the hands-on experience. The facilitator assisted those who had a few challenges during the practical sessions.   

Prof. Jerry John Kponyo lectured on responsible AI. He said participants should be responsible for ensuring that their AI solutions are delivered with integrity, and equity, respecting individuals, and always being mindful of its social impact. 

Prof. Kponyo introduced the FACETS framework as an attempt by the AI research Labs in the AI4D initiative to propose a measure through which responsible AI could be measured. He said the credit for this framework should be given to RAIL in KNUST Ghana, CITADEL in Burkina Faso, and the University of Dodoma Tanzania when used. He added that the governing document, “FACETS Responsible AI Framework”, is proposed to promote and objectively measure the responsible nature of the activities and innovations from AI Labs. The training materials can be accessed from here.