CCMAS Course Search

Solid-state devices and circuits; Programmable controllers; Thyristors; Lasers; Fiber optics ; Power supplies; Op-amp circuits; Open- and closed-loop (feedback) systems; Input devices ;Output devices; AC and DC motors; Motor control devices; Robots and other motion control systems; Data communications.

Flat glass manufacturing process; sheet glass Foucault method, Pittsburgh processes, lof-colbum method. Plate glass. Bithorax semi-continuous casting, PPG ring roll Process continuous horizontal rolling and polishing operations. Patterned glass manufacturing processes. Float glass. Hand production processes where applicable.

Industrial psychology. Principle, practices and problems. African perspective. Nature of work and organisations in Africa. Major deterrent factors. Psychological research in organisation. Personnel selection, Personnel testing in organisations and performance appraisal. Training in industrial organisation. Problems of personnel training. Managerial psychology. Leadership and supervision in organisations. Motivation morale, job satisfaction and incentives. Organisational psychology. Working condition in organisations. Engineering psychology. Human errors, fatigue, accidents and safety. Consumer psychology. Organisational effectiveness.

Fascial spaces and routes of spread. Principles of infection management and antibiotic therapy. Iodontogenic infections and their management. Non-odontogenic infections of soft tissue and their management. Hard tissue infections and their management. Salivary gland infections and their management. Atypical infections of the head and neck and their management. Immune suppression and head and neck infections.

Bacterial infections of the oral cavity. Viral infections of the oral cavity. Mycotic infections of the oral cavity. Diseases of the periodontium. Dental caries. Pulpal diseases, and periapical tissues. Spread of oral infections.

Evaluation of the febrile patient. Epidemiology, prevention and control, aetiological agents in infectious diseases (incubation period, morphology), pathogenesis (acquisition and transmission), laboratory diagnosis, clinical presentation and management and socioeconomic relevance of infectious diseases. Systemic inflammatory response syndrome/sepsis, typhoid fever. HIV/AIDS including epidemiology, pathogenesis, features, asymptomatic or symptomatic infections. diagnosis, opportunistic infections such as tuberculosis and candidiasis, prevention, management and control. Emerging and remerging viral infections, Sars-Cov-2, viral haemorrhagic fevers, malaria, envenomation, snake and scorpion bites, bee stings.

Host-pathogen interactions. Sepsis, systemic inflammatory response syndrome (SIRS), and multi-organ dysfunction syndrome. Viral infectious syndromes. Anaerobic infectious syndromes. Non-tuberculous mycobacterial infections. Diagnosis and treatment of Fungal infections. Infections complicating animal bites.

Introduction to big data. Small data vs. big data. What is big data? The evolution of data/big data. Big data characteristics-3Vs/6Vs. Unique features of big data. Importance of big data? Why does big data matter? Sources of big data. Formats of data. Applications of big data. Use case- issues and solutions. Big data technology. Big data as an opportunity. Example of big data. Big data statistics. Business intelligence vs. big data vs. data mining. Big data handling and techniques. Using the cloud for big data. Big data challenges/problems. How businesses are utilising big data. Big data technologies. Operational and analytical big data. Big data skills. Big data adoption. Big data analysis in practice. Case study session, preparation of case study report and presentation. The big data platform and key aspects. Governance for big data. Big data components. Big data driven organisational change and essential analytical tools and techniques. Develop big data solutions. System and management view of information and big data security. Requirements for information and big data security. Systems-design process and lifecycle security management of information systems. Basic policies on information security and methodologies. Information-security risk management, security policies, security in the systems-engineering process. Laws related to information security and management of operational systems. Apply machine learning techniques and other big data programming languages. Analyse big data recommendations. Cloud-based big data analysis. Lab work: Practice on data acquisition and how to initiate discovery on raw data using discovery systems. Learn Big Data analytics skills. Practical procedure for the crafting of an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from data. Use the practical exercises to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. Hands-on exposure to Hadoop and Spark (or any of the BD tools), build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases. Practical assignment of information and BD security.

Fundamental concepts of innovation and business ideas in general. Product development. Business leadership. Digital marketing. Entrepreneurial opportunities in IT. Legal issues and Business ethics. New venture creation process. Business feasibility planning. Market research. Business strategy. Business models and Business plans. Technical presentations. Report on a successful entrepreneurial outfit.