The School of Mathematics, Statistics and Computer Science (SMSCS) at UKZN is putting its expertise in Data Science and Education to work to provide a brand new Data Science course for second-year students enabling them to learn how to mine data using machine learning.
This course forms part of an initiative by SAS, a leading company specialising in analytics, artificial intelligence and data management software and services, to collaborate with universities in South Africa to fill the Data Science skills gap being created by the exponential growth in advances in digital technologies, big data, and machine learning which are transforming the face of business worldwide.
Using the SAS Viva for Learners (VFL) programme, students taking this new course at UKZN will gain practical experience and skills in data mining, focusing on data classification, clustering and association analysis, interpretation of outputs, and model comparison, contributing to their employability upon graduation. This is a first for an African university, and a source of pride for the SMSCS, which often operates with limited resources to realise its mission of producing capable graduates.
It is just one component of planned interventions by the SMSCS to accelerate its offerings for the training of data scientists. The SMSCS is in the process of establishing a SAS Centre for Data Science for Business at UKZN to offer training and qualifications in Data Science, from undergraduate through to postgraduate level.
Dean and Head of the SMSCS Professor Delia North is driven to ensure the School provides graduates with all they need to be work-ready and meet the needs of the industry. The School has cultivated strong relationships with industry to enable partnerships that enhance the skills of graduates by ensuring the relevance of its programmes in the fast-changing world of work.
Lecturer in Applied Statistics Ms Danielle Roberts noted the value of a hands-on approach to students’ engagement with the course, saying the SAS VFL interface provides excellent insight into new methods and advances in Data Science and creates a space for students to develop these skills.
The VFL programme is also useful for postgraduate students who have made use of it to aid understanding of neural networks and apply different machine learning algorithms.
Lecturer in Statistics, Ms Nombuso Zondo noted that the VFL programme had generated an enthusiastic response among postgraduate students who have enjoyed the programme’s fast response times in producing results, even for complex models and large datasets.
An Applied Statistician in the SMSCS Professor Temesgen Zewotir was thankful for SAS’s support through the VFL programme, saying it will contribute to the School’s advances in Data Science education.
Words: Christine Cuénod
Photograph: Supplied