Bachelor of Science in Computer Science

Course Learning Outcomes

Fundamentals of IT and Computers

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Demonstrate proficiency in using common software applications, including word processing, spreadsheets, and presentation tools, to produce professional documents.
• Explain the basic components and functions of computer hardware and software, demonstrating an understanding of how they interact within a system.
• Analyse different operating systems and their functionalities, including installation, configuration, and troubleshooting.
• Assess various networking concepts, including types of networks, protocols, and security measures, to evaluate their impact on organisational communication.
• Implement basic data management practices, including database creation, querying, and reporting, using appropriate software tools.

Computer and Network Technologies

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Summarise the historical development of cloud computing technologies, demonstrating the ability to guide discussions on their evolution and impact on modern computing practices.
• Evaluate different cloud computing models and platforms, taking responsibility for assessing their advantages and disadvantages in various organisational contexts.
• Differentiate between client and server environments, and assess the benefits of serverless computing, ensuring the ability to advise stakeholders on suitable deployment options.
• Describe network standards, protocols, and topologies, while collaborating with peers to produce comprehensive reports on their relevance in today’s networking landscape.
• Configure networks using routing and switching techniques, monitoring performance to ensure adherence to established standards and best practices.
• Manage projects related to network design and implementation, demonstrating the ability to carry out tasks effectively while authorising changes as necessary to optimize performance.

Database Management System

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Demonstrate a thorough understanding of the advantages and components of Database Management Systems (DBMS).
• Apply the principles of class diagrams and data types to design normalised tables and create a data dictionary.
• Execute and test complex queries using DDL, DML, joins, subqueries, and grouping commands.
• Develop effective forms, reports, and procedural languages for data retrieval, storage, and error handling.
• Manage distributed databases, ensuring robust database administration, security, backup, and recovery processes.

Web and Mobile Application

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Explain modern web and mobile development technologies, frameworks, and hosting solutions.
• Evaluate the impact of development technologies and frameworks on design, functionality, and search engine ranking.
• Review the importance of website design on search engine results and apply search engine optimization (SEO) techniques to improve website ranking.
• Manage the development and deployment of mobile applications within an Integrated Development Environment (IDE), ensuring alignment with functional and technical requirements.

Principal of Computer Programming

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Demonstrate the ability to critically assess how programming practices enhance operational efficiency, foster innovation, and address community challenges.
• Show proficiency in outlining key historical milestones and trends in programming, articulating their significance in shaping modern computing.
• Exhibit competence in defining algorithms and detailing common techniques, such as sorting and searching, to solve computational problems effectively.
• Evaluate the benefits of object-oriented design and explain the use of objects in object-oriented programming.
• Demonstrate the ability to design, implement, and debug an object-oriented software solution, showcasing technical programming skills and problem-solving capabilities.

Software Engineering

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Apply UML and XML to ensure quality, code reuse, flexibility, and modularization in software development, demonstrating expertise in structured design.
• Implement comprehensive test strategies using tools such as Bugzilla, LoadRunner, and Jira, ensuring software quality throughout the development cycle.
• Develop object-oriented programs tailored to business requirements, showcasing the ability to integrate advanced programming concepts like collections and generics.
• Ensure thorough testing and documentation of software, maintaining high standards of accuracy and functionality.

OOPS with Java

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Create objects using constructors, demonstrating an understanding of standard constructors, constructor overloading, and inheritance.
• Handle exceptions effectively in Java, identifying typical scenarios, understanding standard exceptions, and defining custom exceptions.
• Utilise interfaces as programming interfaces in Java, understanding typical scenarios and implementing them effectively.
• Implement polymorphism and encapsulation in Java, showcasing the ability to design flexible and maintainable code.
• Develop comprehensive unit tests for Java applications, ensuring code quality and reliability through effective testing strategies.

Management Information Systems

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Manage the strategic use of IT to support knowledge management, data management, and customer service functions within organisational settings.
• Analyse the impact of IT systems on business functions and organisational structures to align with and achieve organisational objectives.
• Evaluate different types of IT systems and their roles in enhancing business operations, including transaction processing, customer relationship management, and business intelligence.
• Apply quality assurance and control measures to ensure the accuracy and reliability of data for informed decision-making and value creation.

Network Information Systems

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Design various network architectures, including peer-to-peer, client-server, cloud, and virtualized systems, tailored to organisational requirements.
• Configure network services and devices in alignment with business specifications, ensuring seamless connectivity and functionality.
• Implement effective network management practices, including throttling and traffic management, to optimise performance and resource allocation.
• Monitor and troubleshoot network issues using diagnostic tools and techniques to maintain high levels of network availability and reliability.
• Evaluate and adapt network designs to accommodate evolving technologies and business needs, ensuring scalability and efficiency.

Cyber Security

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Define the term ‘cyber security’ comprehensively, covering its scope, objectives, and significance in modern society.
• Explain in detail the processes of identifying, assessing, prioritising, and managing cyber security risks within various organisational contexts.
• Describe and interpret the laws, regulations, and compliance requirements related to cyber security, including GDPR and the Information Security Act.
• Summarise the historical development of cyber security, tracing its evolution from early computer networks to contemporary digital ecosystems.
• Analyse and articulate the multifaceted impacts of cyber security on individuals, organisations, economies, and national security.
• Develop effective strategies and methodologies to stay updated with the latest trends, threats, and best practices in cyber security through continuous learning and community engagement.

Python Primer: An Introduction to Programming with Python

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Demonstrate ability to set up Python environments and utilize them effectively for programming tasks.
• Show proficiency in working with various types of data and variables, utilizing appropriate Python constructs.
• Exhibit ability to write Python code using various programming constructs and effectively handle errors and exceptions.
• Apply Python packages and modules for data analysis and related tasks, enhancing productivity and efficiency.

Mathematics for Computing

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Apply mathematical concepts to analyze and solve computational problems in computer science.
• Ensure accuracy and reliability in data analysis through statistical and probabilistic methods.
• Manage mathematical modeling techniques for effective problem-solving in data science and IT applications.
• Collaborate with teams to integrate mathematical principles into computational and data-driven projects.

Unlocking Big Data: Technologies and Strategies

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Proficiency in employing best practices for big data analytics, including data validation and promoting its value through real-world examples.
• Competence in utilising big data methods and tools such as YARN, HDFS, and MapReduce, demonstrating an understanding of their roles in high-performance architecture.
• Skill in implementing advanced data analytic techniques, including classification and regression, and assessing their applicability to real-world problems.
• Capability to apply concepts related to data stream analysis, including understanding the architecture and models for streaming data.

Introduction to Cryptography

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Deal with security goals and various types of security attacks in digital environments by applying appropriate preventive and responsive measures.
• Recognize applied cryptography in daily life and the rationale behind their usage.
• Demonstrate proficiency in setting up a mobsp server for projects and implementing hash functions in Python programs.
• Apply digital signatures, their security properties, and the ability to generate digital signatures using Python.
• Deal with blockchain technology, including block verification, Bitcoin, and the security requirements of cryptocurrencies.

Exploring the Nexus: Data Science and Artificial Intelligence

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Apply foundational concepts of Data Science and Artificial Intelligence to carry out tasks and solve problems within a practical or professional context.
• Proficiency in identifying and navigating through different stages of a Data Science project.
• Ability to recognize applications of Data Science across various domains and address associated security concerns.
• Skill in implementing Data Science processes including data collection, preprocessing, and model development.
• Competence in applying AI techniques such as searching algorithms, game playing strategies, and machine learning algorithms

Exploring Data Protection and IT Security Measures

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Identify and defend against network attacks by implementing secure layers and configuring SSL/TLS, VPNs, and firewalls.
• Address security issues in distributed systems, including web services and cloud computing, while mitigating cross-site scripting attacks.
• Follow secure system design methodologies to develop secure software and systems.
• Utilise design patterns and formal methods to enhance security in software development.
• Evaluate security measures throughout the software lifecycle to ensure ongoing protection

Understanding Information Security Standards

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Deal with different types of attacks and vulnerabilities in information security, ensuring appropriate mitigation strategies are considered.
• Ability to identify and prioritise security goals for protecting information assets.
• Competence in recognizing and implementing various security services and mechanisms.
• Skill in analysing security risks and developing strategies to mitigate them effectively.
• Capability to assess and enhance the overall security posture of an organisation or system.

Exploring the Internet of Things (IoT)

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Apply basic concepts of the Internet of Things (IoT) to real-world contexts, demonstrating awareness of its purpose and motivation.
• Evaluate the social and economic significance of IoT innovations for consumers and industry, and advise stakeholders on their practical implications.
• Apply data protection principles and ensure security compliance in the design and implementation of IoT systems.
• Select and implement appropriate communication standards, network topologies, and protocols relevant to IoT environments.
• Identify and analyse suitable data storage and processing techniques in networked environments to support IoT applications.

Machine Learning: supervised learning and unsupervised learning

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Proficiency in understanding various learning paradigms and their applications in supervised and unsupervised learning.
• Ability to analyse perspectives and issues related to learning algorithms, including biases and generalisation capabilities.
• Competence in implementing supervised learning algorithms such as decision trees, neural networks, and support vector machines for classification and regression tasks.
• Skill in utilising unsupervised learning techniques such as clustering and dimensionality reduction to discover patterns and structures in data.
• Capability to evaluate and compare different learning algorithms based on their performance metrics and computational complexity.

Data Structure & Algorithm

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Analyse asymptotic notation to compare the efficiency of algorithms.
• Develop data structures such as trees, queues, stacks, and heaps.
• Design advanced searching algorithms, including binary search trees and hash tables.
• Integrate sorting algorithms like insertion sort and quicksort into software applications.
• Implement graph algorithms for depth-first search and connected components.

Exploring the Fundamentals of Web Security

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Analyse the components of the Internet to identify weak points and mitigate security risks.
• Differentiate between HTTP and HTTPS protocols and evaluate their significance for web security.
• Identify various web authentication technologies and their roles in securing web applications.
• Assess recent attack trends and types of web security threats to implement effective defence strategies.
• Distinguish the importance of web application security from network security principles.

Mathematical Modelling

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Apply decay and growth models in linear and nonlinear forms to analyse dynamic phenomena across various fields.
• Develop mathematical models for compartments and population dynamics, applying them to real-world scenarios such as pandemics and financial dynamics.
• Utilise differential equations to model planetary motions, satellite orbits, and circular motion in diverse applications.
• Comprehend and apply basic models and theories of constant-coefficient linear difference equations in economic and financial contexts.

Introduction to Quantum Computing

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Apply the fundamental principles of quantum computation in practical contexts, including the manipulation of qubits and quantum gates.
• Apply principles of quantum mechanics to analyse the states and behaviour of quantum systems.
• Design and implement quantum algorithms for various computational tasks.
• Assess computational complexity and error correction techniques in quantum computation.
• Evaluate and compare different quantum algorithms based on their efficiency and performance.

System Analysis and Designing

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Explain how systems analysis and design contribute to each stage of the software development life cycle, including requirements gathering, design, implementation, testing, and maintenance.
• Identify and describe the key components of systems analysis, including problem identification, feasibility analysis, requirements gathering, and system design.
• Analyse different approaches to system analysis and design, such as structured analysis, object-oriented analysis, and agile methodologies.
• Evaluate system design requirements in terms of functionality, usability, scalability, and security.
• Discuss the importance of each stage in traditional software life cycle approaches and evaluate various software development lifecycle models.
• Differentiate between hard and soft system methodologies and discuss their application in system analysis and design.

Overview of Block chain and its security

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Ensure the integrity of data by recognising the necessity and implications of distributed record-keeping systems.
• Model faults and adversaries within distributed systems, including the Byzantine Generals problem.
• Analyse consensus algorithms to identify scalability challenges and propose solutions for improved performance.
• Evaluate various distributed ledger technologies and their applications in ensuring data transparency and security.
• Implement strategies for fault tolerance and recovery in distributed systems to enhance reliability.

IT Project Management

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Apply the OSI model and TCP/IP operations effectively in network-related tasks and troubleshooting scenarios.
• Manage the implementation and configuration of client-server architecture using socket interfaces in real-world networking environments.
• Apply practical skills in Linux installation and usage.
• Demonstrate adeptness in socket programming using the C language.

E-Commerce

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Identify various e-commerce business models (B2B, B2C, C2C) and their implications for business operations and consumer behaviour.
• Implement e-commerce technologies, including web development tools, payment gateways, and security protocols, to design effective online business solutions.
• Create digital marketing strategies using SEO, social media, and other online marketing techniques to enhance brand visibility and customer engagement.
• Assess legal and ethical issues associated with e-commerce, including data protection regulations and consumer rights, to ensure compliance in online transactions.
• Utilise ecommerce analytics tools to analyse user behaviour and track performance metrics for data-driven decision-making.
• Propose innovative solutions to real-world e-commerce challenges by analysing case studies to enhance operational efficiency and customer satisfaction.

Knowledge Management

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Manage the implementation of knowledge management systems within an organisation to ensure alignment with strategic objectives.
• Supervise teams in executing knowledge-sharing activities that enhance collaboration and innovation.
• Monitor the effectiveness of knowledge management practices and ensure their proper use in decision-making processes.
• Advise stakeholders on best practices and strategies for improving organisational knowledge management.
• Ensure compliance with organisational policies during knowledge-sharing initiatives and knowledge asset utilisation.

Capstone Project

At the end of the Module the learner will have acquired the responsibility and autonomy to:

• Solve intricate challenges in computer science using advanced problem-solving techniques.
• Manage comprehensive projects through effective organisation and execution.
• Apply advanced concepts and tools relevant to specialised fields with technical expertise.
• Assess solutions critically to optimise project outcomes through critical thinking skills.
• Propose innovative approaches and solutions to enhance project effectiveness.
• Navigate uncertainties and obstacles with adaptability and resilience.
• Uphold ethical conduct and professional responsibility throughout project execution.