The innovations brought about by Information and Communication Technology are radically altering our society by changing the way our economy, educational systems, and social and cultural interactions work. This is particularly relevant to the kinds of activities that graduates encounter in their day-to-day personal and professional lives. As this technological innovation progresses, it will become increasingly important to have a knowledge and an understanding of the nature of information and communication technologies, and how they are changing. Anticipating these changes will enhance the choices you make in your personal and working life. Naturally, the more knowledge you have, the more you will be able to exploit the power of Information and Communication Technology. Rhodes University acquired its first computer in , one which was housed in the Department of Physics.
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Computer scientists are experts in computation — both in terms of the theory of computation and its innumerable practical applications. A computer scientist understands how to design and analyze algorithms, how to store and retrieve information, how computers function, and how to develop software systems that solve complex problems. Specialists within computer science might have expertise in developing software applications, in designing computer hardware, or in analyzing algorithms, and in many other current and emerging specializations. Our world-class faculty will challenge you to deepen your intellectual curiosity, and our curriculum will allow you to tailor your computing studies to your specific areas of interest. Along the way, you will develop both algorithmic fundamentals and a framework for understanding that will enable you to keep pace with the ever-changing world of computer science. The computer science program requires students to have a solid foundation in computer software, hardware, and theory, but also gives each student ample opportunity to take advanced electives in areas of computer science such as databases, architecture, networks, artificial intelligence, and graphics, or in emerging interdisciplinary areas such as electronic commerce, web information systems, and computer game design. Enrollment and graduation data.
Meta learning   is a subfield of machine learning where automatic learning algorithms are applied to metadata about machine learning experiments. As of the term had not found a standard interpretation, however the main goal is to use such metadata to understand how automatic learning can become flexible in solving learning problems, hence to improve the performance of existing learning algorithms or to learn induce the learning algorithm itself, hence the alternative term learning to learn. Flexibility is important because each learning algorithm is based on a set of assumptions about the data, its inductive bias. A learning algorithm may perform very well in one domain, but not on the next.
Completing a masters Thesis in computer science is the most challenging task faced by research scholars studying in universities all across the world. As computer science is one of the most vast fields opted by research scholars so finding a new thesis topic in computer science becomes more difficult. With each passing day, new and innovative developments are coming out in this era of mechanization.