About the Author
Tshepo Chris Nokeri a computer scientist and engineer focusing on artificial intelligence (AI), data management and governance, and software engineering. He has over a decade experience spanning in manufacturing, mining, and healthcare sectors. Currently, he serves as ModelOps Engineer at South Africa's largest health risk management services provider and second largest medical aid administrator.He initially completed a Bachelor degree in Information Management, majoring in Information Systems and Business Management. Subsequently, he obtained an Honors degree in Business Science, specializing in Management Science, whereby he graduated top of his class. Concurrently, he received a Master’s degree in Computer Science from the University of the Witwatersrand.Besides his academic qualifications, he embarked in continuous professional development. For instance, he gained certificates in artificial intelligence, big data, cloud computing, business analysis, project management, managerial finance, software law, executive leadership, and corporate governance.He rightfully earned the Oxford University Press Prize Award for obtaining the highest overall marks in the Honor’s degree programme on the first attempt. Equally, he received the TATA Prestigious Scholarship Award and the University of the Witwatersrand Postgraduate Merit Award based on his academic achievements.Besides that, he remains a key contributor in the open-source movement and the field of artificial intelligence through a successful series of book publications with the Springer Nature Company, centered on machine learning, deep learning, forecasting and optimization, natural language processing, and computer vision, with practical implications in fields like finance, economics, healthcare and social sciences.He has over a decade of relevant experience in delivering business and analytical solutions to leading companies in manufacturing, mining, and healthcare sectors. He commenced his professional career as a Information Systems Administrator for a manufacturing company. Subsequently, he established an analytical services company before joining a software consultancy company, where he successfully delivered business solutions to world-renowned petroleum and gas companies. In his present role, he focuses primarily on the governance and life cycle management of a comprehensive range of operationalized AI and decision models, including machine learning, knowledge rules, optimization and agent-based models.Additionally, his long-term experience in programming languages (i.e., Python and R), querying language (i.e., SQL), and statistical and machine learning platforms (i.e., SAS Base, Enterprise Guide and Visual Analytics Studio, Azure Machine Learning Studio, IBM Watson Studio, and AWS SageMaker), including web frameworks and application platform interface technologies, enables me to deliver functional AI-oriented software and web-based applications.
