CCMAS Course Search
Browse BRIDGE's courses under the National Universities Commission's Core Curriculum Minimum Academic Standards (CCMAS) — Nigeria's unified benchmark curriculum for every accredited program. Search by course title, code, faculty or programme to see full descriptions, learning outlines and credit-hour loads.
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CYB 201
2
At the end of this course, students should be able to: 1. explain cybersecurity concepts, its methods, elements, and terminologies of cybersecurity -cyber, security, threat, attack, defence, and operations; 2. describe c...
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Basic concepts: cyber, security, confidentiality, integrity, availability, authentication, access
control, non-repudiation and fault-tolerant methodologies for implementing security. Security
policies, best current practices, testing security, and incident response, Risk management,
disaster recovery and access control. Basic cryptography and software application
vulnerabilities. Evolution of cyber-attacks. Operating system protection mechanisms, intrusion
detection systems, basic formal models of security, cryptography, steganography, network
and distributed system security, denial of service (and other) attack strategies, worms,
viruses, transfer of funds/value across networks, electronic voting, secure applications.
Cybersecurity policy and guidelines. Government regulation of information technology. Main
actors of cyberspace and cyber operations. Impact of cybersecurity on civil and military
institutions, privacy, business and government applications; examination of the dimensions of
networks, protocols, operating systems, and associated applications. Methods and motives of
cybersecurity incident perpetrators, and the countermeasures employed by organisations and
agencies to prevent and detect those incidences. Ethical obligations of security professionals.
Trends and development in cybersecurity. Software application vulnerabilities. Evolution of
cybersecurity and national security strategies, requirements to the typologies of cyber-attacks
that require policy tools and domestic response. Cybersecurity strategies evolving in the face
of big risk. Role of standards and frameworks.
DTS 201
3
At the end of the course, the students should be able to: 1. demonstrate the principles of working with data across distributions, sizes and ranges; 2. explain from first principles the operations that power data-driven...
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Fundamentals of Data Science. Methodology of extracting knowledge from big datasets as
well as various tools and platforms for Data Science. What is Data and why is it important?
Basic classification of Data (Structured, semi-structured and unstructured data), Scope of Data
Science, Steps of Data Science Process: Data collection, Pre-processing, training, and testing.
Rudiments of data visualisations; Distributions, Probability, and Simulations; Predictions and
Models. Use cases in various domains such Image, Natural Language, Audio and Video. Basic
introduction to knowledge extraction: Data mining, Business Intelligence & Knowledge
management, Introduction to Big Data integration and intelligence, Introduction to Data
Analytics, Introduction to programming.
Lab work: Practical experiments on data science process steps in simulated models. Practical
application of the methods and tools used in data science for prediction models with some
simulated exerises. Practical experiments on how to extract knowledge; how to mine valuable
data from large set of data sets using data mining process and methods. Learn how to
integrate business intelligence in big data along with some data analytics pratical exercises.
Simple exercises on R programming to enhance the coding knowledge acquired during theory
class.
ICT 201
2
At the end of the course, students should be able to: 1. identify components of the computer and know-how the components communicate; 2. know the concept of data transfer and memory types and management; 3. be comfortabl...
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Basic principle of computers. Computer "backbone". Data transmission. Random Access
Memory. Permanent Memory. Graphic processing. Communication Ports. Input and Output
Devices. Software types. Accessibility options. Computer types. Portable digital devices.
Network Types. Internet. Instant messaging. Voice over Internet Protocol. Really Simple
Syndication. Network communication. Internet data transfer. Data rate units. Internet access.
Virtual (online) communities. Computer in the workplace. Office Applications (word
processing, spreadsheets, presentation, etc.). Other well-known applications. Telecommuting
(telework).
INS 207
2
At the end of this course, students should be able to: 1. explain system concepts and organisational processes; 2. explain information systems principles and application in modern organisation; 3. describe information te...
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Roles and relevance of information systems in organisations to conduct business and solve
problems. Information systems principles in modern organisations. Systems concepts;
organisational processes; technological aspects of information systems. The internet.
Information technology security. Ethical issues. Database management. Systems development
life cycle.
IFT 205
2
At the end of the course, the students should be able to: 1. explain the history and development of information technologies; 2. describe information technology application domains; 3. identify information technology and...
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Introduction to computer software, hardware, and networking technologies. Information
technology systems model. A brief introduction to information technologies – human-
computer interaction, information management; networking, platform technologies,
programming, and web systems and technologies. Data versus information. History of
information technology and the internet. Information technology application domains.
Security, privacy, policy, and other social issues inherent in Information technology
development and use. Future trends in information technology, problems on mining,
visualisation, natural language processing, and Blockchain.
MTH 209
2
At the end of the course, students should be able to: 1. solve some numerical solutions of algebraic and transcendental equations; 2. describe curve fitting; 3. discuss error analysis; 4. calculate interpolation and appr...
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Solution of algebraic and transcendental equations. Curve fitting. Error analysis. Interpolation
and approximation. Zeros of non- linear equations ‘in one variable’. Systems of linear
equations. Numerical differentiation and integration. Initial value problems in ordinary
differential equations.
DTS 211
3
At the end of the course, the students should be able to: 1. utilise the R programming language for data-driven functions and utilities that have been lauded across the computing industry; 2. explain the structures, func...
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History and Overview of R, Installation, Introduction to R and RStudio, R interface, Cleaning
and transforming data, Getting data in and out of R, Evaluation, R Objects, Numbers,
Attributes, Vectors, Matrices/Arrays, Lists, Factors, Missing Values, Data Types, Structures and
Frames, Names, , Displaying and plotting data, Reading lines of a Text File, Reading from a
URL connection, Vectorised Operations, Dates and Times, Control Structures, Functions,
Scoping Rules, Coding Standard for R, Looping, Debugging, Profiling R Code. Creating data
products using R package.
Lab work: Installation of R programming language and learning the practical basics. Practical
programming exercises on R programming language in getting data in and out, evaluation,
computation, finding missing values and reading lines of text files. Practical exercises on R
coding and debugging.
SEN 201
2
At the end of this course, students should be able to: 1. describe the concept of the software life cycle; 2. explain the phases of requirements analysis, design, development, testing and maintenance in a typical softwar...
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Software Engineering concepts and principles. Design, development and testing of software
systems. Software processes: software lifecycle and process models. Process assessment
models. Software process metrics. Life cycle of software system. Software requirements and
specifications. Software design. Software architecture. Software metrics. Software quality and
testing. Software architecture. Software validation. Software evolution: software
maintenance; characteristics of maintainable software; re-engineering; legacy systems;
software reuse. Software Engineering and its place as a computing discipline. Software project
management: team management; project scheduling; software measurement and estimation
techniques; risk analysis; software quality assurance; software configuration management.
Software Engineering and law.
SEN 201
2
At the end of this course, students should be able to: 1. describe the concept of the software life cycle; 2. explain the phases of requirements analysis, design, development, testing and maintenance in a typical softwar...
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Software Engineering concepts and principles. Design, development and testing of software
systems. Software processes: software lifecycle and process models. Process assessment
models. Software process metrics. Life cycle of software system. Software requirements and
specifications. Software design. Software architecture. Software metrics. Software quality and
testing. Software architecture. Software validation. Software evolution: software
maintenance; characteristics of maintainable software; re-engineering; legacy systems;
software reuse. Software Engineering and its place as a computing discipline. Software project
management: team management; project scheduling; software measurement and estimation
techniques; risk analysis; software quality assurance; software configuration management.
Software Engineering and law.
300 Level
SEN 201
2
At the end of this course, students should be able to: 1. describe the concept of the software life cycle; 2. explain the phases of requirements analysis, design, development, testing and maintenance in a typical softwar...
View learning outline
Software Engineering concepts and principles. Design, development and testing of software
systems. Software processes: software lifecycle and process models. Process assessment
models. Software process metrics. Life cycle of software system. Software requirements and
specifications. Software design. Software architecture. Software metrics. Software quality and
testing. Software architecture. Software validation. Software evolution: software
maintenance; characteristics of maintainable software; re-engineering; legacy systems;
software reuse. Software Engineering and its place as a computing discipline. Software project
management: team management; project scheduling; software measurement and estimation
techniques; risk analysis; software quality assurance; software configuration management.
Software Engineering and law.
300 Level