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BACHELOR OF SCINCE IN COMPUTER SCIENCE

COURSE OUTLINE

FIRST YEAR - SEMESTER ONE
BACKGROUND AND RATIONALE

Computer systems and internet technologies module introduces learners to computer systems and internet technologies. The module starts with an explanation on understanding information as a resource including, legal, ethical and privacy issues and security aspects. It explains the categories of information systems and the level of support that they provide, it explains how business transactions take place, explains the growth of electronic commerce, the architecture of the Web, URL, web servers and HTTP. The module further describes the practical introduction to HTML5 – creating Web pages incorporating media, explains the HTML forms and basic use of client side scripting (such as JavaScript) for input validation. The module also explains the theoretical overview of the client server environment to support the practical use of HTML 5 and JavaScript. The module equally gives an introduction to cloud based systems, such as storage and cloud based operating systems and ends with a Case studies involving the Chromebook and the university virtual desktop..

LEARNING OUTCOMES At the end of this module learners should be able to:
1. Know and explain how information is a resource including, legal, ethical and privacy issues and security aspects.
Know and describe the categories of information systems and the level of support that they provide
2. Know and apply knowledge on how business transactions take place using computer systems.
3. Know and describe the growth of electronic commerce, the architecture of the Web, URL, web servers and HTTP.
4. Know and apply the knowledge on HTML5 in creating Web pages and incorporating media.
5. Know and describe the HTML forms and basic use of client side scripting (such as JavaScript) for input validation.
6. Know and apply the theoretical overview of the client server environment to support the practical use of HTML 5 and JavaScript.
7. Know and apply cloud based systems, such as storage and cloud based operating systems
COURSE CONTENT
  • UNIT 1: Understanding information as a resource including, legal, ethical and privacy issues and security aspects.
  • UNIT 2: Categories of information systems and the level of support that they provide.
  • UNIT 3: How business transactions take place
  • UNIT 4: The growth of electronic commerce
  • UNIT 5: The architecture of the Web, URL, web servers and HTTP.
  • UNIT 6: Practical introduction to HTML5 – creating Web pages incorporating media.
  • UNIT 7: HTML forms and basic use of client side scripting (such as JavaScript) for input validation
  • UNIT 8: Theoretical overview of the client server environment, to support the practical use of HTML 5 and JavaScript.
  • UNIT 9: An introduction to cloud based systems, such as storage and cloud based operating systems.
  • Third item
  • UNIT 10: Case studies involving the Chromebook and the university virtual desktop.
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGS

Douglas E. Comer (2009). Computer Networks and Internet. London: Pearson Education Group Douglas E. Comer (2014). Fundamentals of Computer Networking and Internetworking. Purdue University

BACKGROUND AND RATIONALE

Organizational and Managerial Communication provides an overview of the role that communication plays in business culture(s). From memos and emails to informal chats with colleagues and formal presentations, communication processes saturate how we interact at the professional level. In this course, students will build a foundation for understanding and deploying strategic messages. Throughout the semester, we will discuss key issues in organizational culture, with particular attention to analyzing situations critically and communicating strategically as members of the various kinds of organizations in which we participate.

LEARNING OUTCOMES

At the end of this unit, you should be able to:


  • explain when one has really communicated, i.e., when a piece of communication has actually taken place
  • list and describe the general kinds of communication and particular forms of practical communication
  • identify the qualities of effective communication
  • Explain the barriers to effective communication.
COURSE CONTENT
  • 1. Definition
  • 2. Kinds of Communication
  • 3. General Kinds of Communication
  • 4. Common Forms of Practical Communication
  • 5. Purposes or Functions of Communication
  • 6. Qualities of Effective Communication
  • 7. Barriers to Effective Communication
  • 8. Conclusion
  • 9. Summary
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGS

Breth, Robert D. (latest edition). Dynamic Management Communications. Reading (Massachusetts): Addison Wesley Publishing Co. Ltd. Evans, Desmond W. (latest edition). People and Communication, (2nd Ed.). London: Pitman Publishing.

BACKGROUND AND RATIONALEProgramming Foundations module introduces learners to the foundations of programming. The module starts with explaining variables and data Types in programming, it explains the concept of decisions and selection in programming, explains the functions and parameters, explains debugging, explains Loops and Iteration, explains lists and dictionaries/Maps, strings and string manipulation, files and input/output and ends with explaining graphical user interfaces.
LEARNING OUTCOMESAt the end of this unit, you should be able to:
  • Know and describe variables and data Types in programming
  • Code non-trivial programs in a modern programming language
  • Know and apply concepts of decisions and selection in programming
  • Know and apply the concepts of parameters in programming
  • Know and apply knowledge on debugging in programming
  • Know and apply the principles of loops and iteration
  • Know and apply the usage of lists and dictionaries/Maps in programming
  • Know and apply the use of strings and string manipulation in programming
  • Know and apply the use of files and input/output in programming
  • Know and apply knowledge on usage of graphical user interfaces
COURSE CONTENT
  • UNIT 1: Variables and Data Types
  • UNIT 2: Decisions and Selection
  • UNIT 3: Functions and Parameters
  • UNIT 4: Debugging
  • UNIT 5: Loops and Iteration
  • UNIT 6: Lists and Dictionaries/Maps
  • UNIT 7: Strings and String Manipulation
  • UNIT 8: Files and Input/Output
  • UNIT 9: Introduction to Graphical User Interfaces
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSRhodes B and Goerzen J (2014). Foundations of Python Network Programming. New York: Brandon Rhodes and John Goerzen Adam Stewart (2016). Python Programming: Python Programming for Beginners. Adam Stewart.
BACKGROUND AND RATIONALEPrinciples of Security module introduces learners to principles of security in computing. The module starts with explaining issues, threats and their impact on a business environment, it explains risk management, business Continuity, contingency planning and disaster recovery planning, explains compliance with standards/the law/regulatory framework and ends with explaining professional and ethical codes of conduct in computing.
LEARNING OUTCOMESAt the end of this unit, you should be able to:  
  • Know and describe the information systems threats, vulnerabilities and risks
  • Know and apply the knowledge in the management of, creating/maintaining a security policy
  • Know and apply methods of deploying security controls/methods/technologies
  • Know and apply the courses of action in solving problems in real-world security scenarios
  • Know and follow the security acts and standards and codes of conduct
COURSE CONTENT
  • UNIT 1: Issues, threats and their impact on a business environment.
  • UNIT 2: Risk Management:
    2.1 Identification and analysis techniques as well as control strategies.
  • UNIT 3: Business Continuity: Contingency planning and disaster recovery planning.
  • UNIT 4: Compliance with standards/the law/regulatory framework:
    4.1 Information Security Policy: ISO27001 all sections,
    4.2 ICT Legislation (Zambian).
  • UNIT 5: Professional and ethical codes of conduct:
    5.1 ACM,
    5.2 BCS
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSThomas A. Johnson. (2015). CYBER-SECURITY: Protecting Critical Infrastructures from Cyber Attack and Cyber Warfare. Boca Raton, Florida: CRC Press
FIRST YEAR - SEMESTER TWO
BACKGROUND AND RATIONALEElectronic Government introduces leaners to new trends in public service delivery using information and communication technology. The module beings with an introduction on what E-government is, explains the concept of Egovernment in development models, examines the different regional and international policies on e-governance. The module further examines and explains the E-government Development Index, examines the Legislation and Policies on E-government Development and finally explains the Telecommunication Policy in Zambia.
LEARNING OUTCOMESAt the end of this module learners should be able to: 1. Know and explain how information is a resource including, legal, ethical and privacy issues and security aspects. Know and describe the categories of information systems and the level of support that they provide 2. Know and apply knowledge on how business transactions take place using computer systems. 3. Know and describe the growth of electronic commerce, the architecture of the Web, URL, web servers and HTTP. 4. Know and apply the knowledge on HTML5 in creating Web pages and incorporating media. 5. Know and describe the HTML forms and basic use of client side scripting (such as JavaScript) for input validation. 6. Know and apply the theoretical overview of the client server environment to support the practical use of HTML 5 and JavaScript. 7. Know and apply cloud based systems, such as storage and cloud based operating systems
COURSE CONTENT
  • Unit 1 Introduction to E-Governance
  • Unit 2 E-Government Development Models.
  • Unit 3: Regional and Global Trends
  • Unit 4. The E-government Development Index
  • Unit 5. Legislation and Policies on E-government Development
  • Unit 6. Telecommunication Policy in Zambia
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSFang, Z., (2002). E-government in Digital Era: Concept, Practice, and Development. International Journal of the Computer, the Internet and management, 10(2), pp.1-22.
BACKGROUND AND RATIONALESoftware Engineering module introduces learners to software engineering. The modules begins with explaining key concepts in software engineering, explains the concept of tools and environments, explains the process of project management, explains software process models, explains the process of software analysis and design using UML, explains software requirements, analysis, validation and management. The module further explains software design, design concepts, design patterns. It also explain software testing, testing approaches, testing levels (unit, integration, system, acceptance), it explains software analysis, program optimisation and correctness, static and dynamic analysis, explains software maintenance, corrective, adaptive, perfective and preventive maintenance, explains software quality management, assurance, planning, control, and ends with explaining agile software development, methods and practices.
LEARNING OUTCOMESAt the end of this unit, you should be able to:
  • Know and apply key concepts of the analysis, design, development and maintenance of complex software systems and infrastructures.
  • Know and apply knowledge on the software lifecycle and its stages and utilise these in the development of software process models.
  • Know and knowledge in conducting software tests in order to evaluate and verify software products.
  • Know and apply the knowledge in software analysis, program optimisation and correctness, static and dynamic analysis
  • Know and apply the knowledge in software maintenance, corrective, adaptive, perfective and preventive maintenance
  • now and apply knowledge on software quality management, assurance, planning, control
  • Know and apply the knowledge in agile software development methods and practices.
COURSE CONTENT
  • UNIT 1: Key concepts in Software Engineering.
  • UNIT 2: Tools and Environments.
  • UNIT 3: Project Management.
  • UNIT 4: Software Process Models.
  • UNIT5 : Software Analysis and Design using UML.
  • UNIT 6: Software Requirements, analysis, validation and management.
  • UNIT 7: Software Design, design concepts, design patterns.
  • UNIT 8: Software Testing, testing approaches, testing levels (unit, integration, system, acceptance).
  • UNIT 9: Software Analysis, program optimisation and correctness, static and dynamic analysis.
  • UNIT 10: Software Maintenance, corrective, adaptive, perfective and preventive maintenance.
  • UNIT 11: Software Quality Management, assurance, planning, control.
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSBovee, C.L. & Thill, J.V. (2014). Business communication essentials (6th). Boston: Pearson.
BACKGROUND AND RATIONALEData Science module introduces learners to data science. The module combines topics from Computer Science and Mathematics and has a significant presence in many areas of science and technology. The module begins with Introducing data science and its key concepts. It explains data points, datasets, data types. It describes the applications of data science. Explains the mathematical concepts underpinning data science. It describes statistical analysis, aggregate data. The module further describes statistical distributions. It explains the utilising of linear algebra for solving data science related problems. It explains the process of visualising data, design principles in data visualisation. It further explains visual storytelling in data science. Explains data clustering, analysis, algorithms and visualisation. The module explains the concept of connected data, introduction to graph theory, initialising and processing connected data, visualising networks and ends with explaining the process of machine learning, applications, algorithms, supervised, unsupervised learning.
LEARNING OUTCOMESAt the end of this unit, you should be able to:
  • Know and explain scope of data science and its key concepts, from academic, scientific and industrial point of view.
  • Know and apply the mathematical concepts underpinning data science.
  • Know and apply statistical analysis and aggregate data to solve data science related problems.
  • Know and explain statistical distributions in data science.
  • Know and apply linear algebra for solving data science related problems
  • Know and explain the process of visualizing data and design principles in data visualization
  • Know and apply data science in visual storytelling.
  • Know and explain the process of data clustering, analysis, algorithms and visualization.
  • Know and explain the concept of connected data, graph theory, initializing and processing connected data and visualising networks.
  • Know and explain the process of machine learning, applications, algorithms, supervised and unsupervised learning.
COURSE CONTENT
  • UNIT 1: Introduction to Data Science and its key concepts.
  • UNIT 2: Data points, datasets, data types.
  • UNIT 3: Applications of Data Science.
  • UNIT 4: Mathematical concepts underpinning Data Science.
  • UNIT 5: Statistical analysis, aggregate data.
  • UNIT 6: Statistical distributions.
  • UNIT 7: Utilizing Linear Algebra for solving Data Science related problems.
  • UNIT 8: Visualizing data, design principles in Data Visualization.
  • UNIT 9: Visual Storytelling in Data Science.
  • UNIT 10: Data Clustering, analysis, algorithms and visualization.
  • UNIT 11: Connected data, introduction to Graph Theory, initializing and processing connected data, visualizing networks.
  • UNIT 12: Machine Learning, applications, algorithms, supervised, unsupervised learning.
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSEric Goh Ming Hui (2019). Learn R for Applied Statistics With Data Visualizations, Regressions, and Statistics. Singapore: Eric Goh Ming Hui Thomas Mailund (2017). Beginning Data Science in R Data Analysis, Visualization and Modelling for the Data Scientist. Aarhus, Denmark: Thomas Mailund
BACKGROUND AND RATIONALEMathematics for Computer Science module introduces learners to mathematics for computer science. The module begins with explaining sets, Venn diagrams, etc. numbers, algebra and number bases, modular arithmetic, 2’s complement. Explains the concepts of logic, truth tables and proofs. Explains the process of pattern matching and unification. Explains the concept of graphs, functions, relations and mappings. Explains vectors, matrices and trigonometry and ends with explaining data visualization, introductory probability and introductory statistics.
LEARNING OUTCOMESAt the end of this unit, you should be able to:  
  • Demonstrate an understanding of sets, logic, graph theory and discrete mathematics algorithms and their applications in computing.
  • Understand vectors and matrices and apply them to a range of problems and apply arithmetic and algebraic expressions in a range of number types and bases.
  • Apply basic principles of statistics and probability and use software for data analysis and data visualization and be able to interpret results.
COURSE CONTENT
  • UNIT 1: Sets, Venn Diagrams, etc. Numbers, Algebra and Number bases, modular arithmetic, 2’s complement.
  • UNIT 2: Introduction to Logic, truth tables, Proofs.
  • UNIT 3: Introduction to pattern matching and unification.
  • UNIT 4: Introduction to Graphs, Functions, Relations, Mappings..
  • UNIT 5: Vectors & Matrices, trigonometry.
  • UNIT 6: Data visualization, introductory probability, introductory statistics.
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSY.N Singh (2005). Mathematical Foundation of Computer Science. New Delhi: New Age International Publishers Malik D.S and Sen M.K (2004). Discrete Mathematical Structures: Theory and Applications. Boston: Thomson Learning
SECOND YEAR - SEMESTER ONE
BACKGROUND AND RATIONALEApplication Development module introduces learners to application development process. Understanding of programming techniques is essential for practitioners across computer science and IT disciplines. Building on programming skills and experience with UML and object oriented languages; this module considers advanced object oriented techniques together with issues of user interface design, software re-use, software quality and a structured approach to software design and implementation. Emphasis is placed on use of modern integrated development environment to develop data-driven applications with a graphical user interface. Programming techniques will be taught following a problem solving, case-study based approach to learning programming skills
LEARNING OUTCOMESAt the end of this module, learners should be able to:
  • Know and explain the features of object-oriented programming languages, comparison and evaluation of programming languages.
  • Know and apply practical knowledge of UML
  • Know and apply UML knowledge to design object oriented, interactive, data-driven, applications.
  • Know and apply knowledge of modern IDE with an object oriented programming language to create interactive, data-driven, applications.
  • Know and demonstrate knowledge of theoretical and practical skill in the design, implementation and testing of applications making use of object oriented approaches such as classes, message passing, overloading, data connectivity, inheritance, threads and patterns
COURSE CONTENT
  • UNIT 1: Features of object-oriented programming languages, comparison and evaluation of programming languages.
  • UNIT 2: UML in practice: class, component, activity, use case, sequence and state diagrams.
  • UNIT 3: Use of an Integrated Development Environment to implement UML based designs.
  • UNIT 4: Events, errors and exceptions, classes revisited.
  • UNIT 5: Inheritance, containers and collections.
  • UNIT 6: User interface design, facilities for building GUI interfaces, user input validation.
  • UNIT 7: Database connectivity, querying and protection.
  • UNIT 8: Multithreading, issues of concurrency.
  • UNIT 9: Debugging and testing of object-oriented programs, TDD.
  • UNIT 10: Object Oriented design patterns.
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSSeppe vanden Broucke and Bart Baesens (2018). Practical Web Scraping for Data Science: Best Practices and Examples with Python. Leuven: Seppe vanden Broucke and Bart Baesens
BACKGROUND AND RATIONALEProfessional Project Management module introduces learners to professional project management. The module provides a thorough understanding of project management principles, tools and techniques with specialisation in IT based projects. The module explains the process of project, programme and portfolio management. It describes the critical path method (activity on node, activity on arrow), explains the process of project risk evaluation as well as mitigation; explains the process of data protection, highlights the relevant laws on computer misuse; describes malicious communications; highlights the concept of copyright and intellectual property; and ends with explaining the current software tools, including Microsoft project.
COURSE CONTENT
  • UNIT 1: Project, Programme and Portfolio Management
  • UNIT 2: Critical Path Method (activity on node, activity on arrow)
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSKim Heldman (2018). PMP: Project Management Professional Exam Study Guide. Indianapolis: John Wiley and Sons
BACKGROUND AND RATIONALEUser interface design module introduces learners to interface design. The module starts by explaining the current theories, practices and principles of user interface design and evaluation. It explains how user-centred design helps in building user interfaces which are accessible, ease to learn and user friendly. It explains the concept of colour theory, front terminology, layout and graphic designs elements in visual user interface design.
LEARNING OUTCOMESAt the end of this unit, you should be able to:
  • Know and explain the issues, principles and practices involved in developing and evaluating interfaces for interactive applications
  • Know and demonstrate awareness of human-computer interface standards and guidelines
  • Know and apply appropriate principles, concepts and models within a user-centred design process for the development and evaluation of interactive system interfaces
  • Know and apply the knowledge in designing solutions that are suitable to different users and contexts
  • Know and explain the ethical and social implications of policies, legal and professional standards and codes of conduct to the design of user interfaces
  • Know and explain the impact of user interface on the individual and society.
COURSE CONTENT
  • UNIT 1: HCI context;
  • UNIT 2: Principles of graphical user interfaces (GUIs);
  • UNIT 3: Managing design processes for user-centred design;
  • UNIT 4: User research and user personas;
  • UNIT 5: Ideation and prototyping;
  • UNIT 6: Information Architecture;
  • UNIT 7: Standards,
  • UNIT 8: guidelines, principles and theories;
  • UNIT 9: Design patterns;
  • UNIT 10: Designing for different devices;
  • UNIT 11: Evaluating interface designs (e.g. usability, heuristics);
  • UNIT 12: Interface visual design (e.g. colour, fonts, layout) and interaction methods;
  • UNIT 13: Accessibility design;/li>
  • UNIT 14: Contemporary and emergent interactive technologies (e.g. touch, speech, VR).
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSDix A, Findlay J, Abowd G.D and Beale R (2004) Human Computer Interaction. Harlow: Pearson Education
BACKGROUND AND RATIONALEWeb Programming module introduces learners to web programming. The module starts with explaining the process of reviewing HTML/CSS and HTML Forms, client/server relationship and HTTP client-side scripting and CSS frameworks. The module then explains the relational databases that is, creating, updating and normalization in MySQL, server-side PHP PDO programming. It explains the concept of website security including basic data encryption. Explains the process of Content Management systems. Explains the process of accessibility and user-testing then ends with explaining the ethical, legal and social Issues in web programming.
LEARNING OUTCOMESAt the end of this unit, you should be able to:  
  • Know and explain the process of reviewing HTML/CSS and HTML Forms, client/server relationship and HTTP client-side scripting and CSS frameworks.
  • Know and explain the concept of website security including basic data encryption..
  • Know and explain the process of content management systems.
  • Develop a web application with relational database connectivity using a variety of technologies, specifically HTML5, PHP PDO and MYSQL
  • Know and explain issues surrounding Internet and intranet technologies, such as browser dependency, accessibility, legal and security concerns.
  • Critically analyse and evaluate Internet related business problems.
COURSE CONTENT
  • UNIT 1: Review of HTML/CSS and HTML Forms. Client / Server relationship – HTTP Client-side scripting and CSS frameworks
  • UNIT 2: Relational databases: creating, updating and normalisation in MySQL, Server-side PHP PDO programming.
  • UNIT 3: Website security including basic data encryption.
  • UNIT 4: Understanding of Content Management Systems.
  • UNIT 5: Accessibility and user-testing.
  • UNIT 6: Ethical, Legal and Social Issues.
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSSven Lennartz and Vitaly Friedman (2011). Mastering Photoshop for Web Designers. Freiburg: Smashing Media
THIRD YEAR - SEMESTER ONE
BACKGROUND AND RATIONALEAdvanced Programming module introduces learners to advanced programming. The module starts with explaining the concept of programming with threads, it explains the process of programming using reflection, explains the process of creating software components, explains the concept testdriven development (e.g. with JUnit), explains concept of version control and building tools (e.g. Git), explains the process of creating generic classes, explains the concept of design patterns, explains the process of building libraries and ends with explaining the concept of lambda expressions.
LEARNING OUTCOMESAt the end of this module, learners should be able to:
  • Use professional techniques for code and design reuse such as library creation, application of design patterns and development of software components.
  • Know and describe the categories of information systems and the level of support that they provide
  • Apply advanced programming techniques such as threads, reflection and generic classes, basic distributed programming techniques, object relational mapping.
  • Make appropriate use of software engineering tools and techniques such as test-driven development, version control, generation of documentation, build-tools
COURSE CONTENT
  • UNIT 1: Programming with threads
  • UNIT 2: Using reflection
  • UNIT 3: Creating software components
  • UNIT 4: Test-driven development (e.g. with JUnit)
  • UNIT 5: Version control and build tools (e.g. Git)
  • UNIT 6: Creating Generic classes
  • UNIT 7: Design patterns
  • UNIT 8: Building libraries.
  • 9UNIT: Lambda expressions
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSAdam Stewart (2016). Python Programming: Python Programming for Beginners. Adam Stewart Fabio Nelli (2015). Python Data Analytics: Data Analysis and Science Using Pandas, matplotlib, and the Python Programming Language. Fabio Nelli
BACKGROUND AND RATIONALEInformation Analysis and Visualization introduces learners to information analysis and visualization. The module starts with explaining the fundamental concepts in information visualization. It then explains the principles of good design practices in information visualization. It describes the different types of information visualization and the options for using them. It explains the concept of Interactive tools for information visualization and dashboards. Explains the process of visual analytics for identifying trends and patterns in datasets then ends with explaining the practical experience of data exploration.
COURSE CONTENT
  • Identify and apply fundamental concepts related to information analysis & visualization.
  • Demonstrate knowledge of the different types of information visualization and identify appropriate types of visualization for various types of data.
  • Apply analytical & visualization tools & techniques to obtain insight from datasets.
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSJosiane Zerubia Gabriele Moser (2018). Mathematical Models for Remote Sensing Image Processing: Models and Methods for the Analysis of 2D Satellite and Aerial Images. Cham, Switzerland: Springer International Publishing
BACKGROUND AND RATIONALEData Structures and Algorithms module introduces learners to data structures and algorithms. This module begins with explaining the theoretical foundations and the practical skills to design and develop software solutions. It then proceeds to explaining the process of manipulating a range of data structures. It then describes the well-known algorithms which process various types of data structures, it proceeds to explain the process of designing implementing and testing algorithms. The module proceeds to explaining the process of developing and improving algorithms and ends with explaining how algorithms can be used to solve advanced real-world data science related tasks.
LEARNING OUTCOMESAt the end of this unit, you should be able to:
  • Utilise and evaluate the acquired theoretical knowledge of various data structures and the corresponding algorithms which manipulate them.
  • Design, develop and test software solutions, which successfully process various data structures.
  • Further develop popular algorithms into advanced solutions which solve real-world data related problems.
COURSE CONTENT
  • UNIT 1: Data Types
  • UNIT 2: Character Strings
  • UNIT 3: Abstract Data Types
  • UNIT 4: Control Flow Statements
  • UNIT 5: Complexity of Algorithms (Big O Notation).
  • UNIT 6: Iterative Algorithms.
  • UNIT 7: Recursive Algorithms.
  • UNIT 8: Linear Data Structures: Arrays, Stacks, Queues, Linked Lists.
  • UNIT 9: Non-Linear Data Structures: Graphs, Trees
  • UNIT 10: Maps and Hash Tables.
  • UNIT 11: Sorting Algorithms.
  • UNIT 12: Optimization Algorithms/Approaches.
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSNarasimha Karumanchi (2016). Data Structures and Algorithmic Thinking with Python. Career Monk Publications Michael T. Goodrich, Roberto Tamassia and Michael H. Goldwasser (2013). Data Structures and Algorithms in Python. Hoboken: John Wiley and Sons
BACKGROUND AND RATIONALEHuman Computer Interaction and Design module introduces learners to human computer interaction and design. The module begins with explaining the technical knowledge and skills necessary for designing effective human computer interactions and carrying out user-centred design activities to inform the creation of systems and applications. The module further explains the process of experiencing managerial issues affecting the development of human-computer interactions, and ends with explaining the relevant legal, social, ethical and professional issues in human computer interactions.
LEARNING OUTCOMESAt the end of this unit, you should be able to:  
  • Deploy theory, design principles, tools and methodologies to implement and evaluate human- computer interactions
  • Carry out design research to inform development of systems and applications
  • Construct and create prototypes of human-computer interactions
  • Demonstrate the origins of ideas by correctly citing and referencing sources used in the work
COURSE CONTENT
  • UNIT 1: Review of HTML/CSS and HTML Forms. Client / Server relationship – HTTP Client-side scripting and CSS frameworks
  • UNIT 2: Relational databases: creating, updating and normalisation in MySQL, Server-side PHP PDO programming.
  • UNIT 3: Website security including basic data encryption.
  • UNIT 4: Understanding of Content Management Systems.
  • UNIT 5: Accessibility and user-testing.
  • UNIT 6: Ethical, Legal and Social Issues.
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSTheodor Wyeld Paul Calder and Haifeng Shen (2015). Computer-Human Interaction: Cognitive Effects of Spatial Interaction, Learning, and Ability. Switzerland: Springer International Publishing David Benyon (2014). Designing Interactive Systems: A comprehensive guide to HCI, UX and interaction design. London: Pearson Education
THIRD YEAR - SEMESTER TWO
BACKGROUND AND RATIONALERequirements and Management module introduces learners to requirements management. Quality Information systems are critical to the success of today’s organisations. Underpinning the development of such quality systems is the successful management of the requirements engineering cycle. This module therefore first examines the key issues associated with the successful management of requirements. It further explains a number of practical tools and techniques used to overcome these issues.
LEARNING OUTCOMESAt the end of this module, learners should be able to:
  • Analyse and compare current approaches to requirements management within a development environment.
  • Assess the impact of stakeholders and organisational culture on the development of effective requirements and system development.
  • Relate issues associated with risk, quality, and Legal/Social/Ethical/Professional (LSEPI) to a practical scenario.
COURSE CONTENT
  • UNIT 1: Core concepts in requirements engineering management
  • UNIT 2: Management Requirements Engineering and people
  • UNIT 3: Elicitation and Modelling requirements (review)
  • UNIT 4: Managing requirements in an agile environment
  • UNIT 5: Version control and build tools (e.g. Git)
  • UNIT 6: Creating Generic classes
  • UNIT 7: Design patterns
  • UNIT 8: Building libraries.
  • 9UNIT: Lambda expressions
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSKarl E. Wiegers (2009). Software Requirements: Practical Techniques for Gathering and Managing Requirement throughout the Product Development Cycle. Karl Wiegers Axel van Lamsweerde (2009). Requirements Engineering: From System Goals to UML Models to Software Specifications. West Sussex: John Wiley and Son
BACKGROUND AND RATIONALEComputing Education and Communication introduces learners to computing education and communication. The module aims to develop a range of skills in the learners and to present them with an opportunity to experience a taste of teaching especially for those interested in teaching as a career. The module will guide learners to work in a school/college at least once a week for a semester. The module inspires learners to be role models to school pupils which will also help to improve results in general by providing assistance in to the pupils.
LEARNING OUTCOMES At the end of this module learners should be able to:
  • Analyse and evaluate the standard teaching methods and be able to prepare lesson plans and teaching materials.
  • Understand the needs of individuals, and to handle difficult and potentially disruptive situations in a classroom.
  • Retain and improve on key employability skills such as public speaking, organisational, prioritising, negotiating and critical reporting skills.
  • Improvise, give (and receive) feedback.
  • Understand staff responsibilities and possess interpersonal skills when dealing with colleagues.
  • Critically reflect on personal experience in school/college and on practical issues in the classroom.
COURSE CONTENT
  • UNIT 1: introduction to working with children,
  • UNIT 2: conduct in the school environment,
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSJon Woodcock (2016). Coding Projects in Scratch: A step-by-step visual guide to coding your own animations, games, simulations and more. London: Penguin Random House
BACKGROUND AND RATIONALEInformation and Content Management module introduces learners to information and content management. The module begins with explaining the necessary knowledge and skills in management of content for enterprise-wide websites and intranets. It explains the necessary knowledge of implementation and governance of established systems.
LEARNING OUTCOMESAt the end of this unit, you should be able to:
  • Critically evaluate web-based Content Management Systems
  • Design and build a web or intranet site for an organisation
  • Demonstrate understanding of implementation and governance of a CMS
  • Communicate clearly and effectively, in a range of forms, taking account of different audiences
COURSE CONTENT
  • UNIT 1: Information as a resource in large enterprises;
  • UNIT 2: Information Architecture of enterprise web sites and intranets;
  • UNIT 3: Security issues in Content Management Systems;
  • UNIT 4: Information Management Policies;
  • UNIT 5: Requirements specifications and Testing for Content Management.
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSCarlos Coronel, Steven Morris and Peter Rob (2011) DATABASE SYSTEMS: Design, Implementation and Management Boston: Cengage Learning. Vijay Krishna Pallaw (2010). DATABASE MANAGEMENT SYSTEMS. New Delhi: Kamal Jagasia Robert D. Stueart and Barbara B. Moran (2007). Library and Information Center Management. Connecticut: Greenwood Publishing Group
BACKGROUND AND RATIONALENetwork Technology module introduces learners to network technology. The module begins with explaining the network technologies necessary to make informed selections for particular scenarios, explains the principles of network performance and the factors that influence it. The module further explains the practical aspects of network technologies and their operational characteristics, strengths and weaknesses. The module further does a comparison examines the different technologies and does a contrast of among them to establish appropriate technologies and configurations that meet needs of organisations.
LEARNING OUTCOMESAt the end of this unit, you should be able to:
  • Investigate network technology through simulation.
  • Investigate the effects of various network traffic conditions on network performance.
  • Gain experience and apply the knowledge in carrying out an experiment, to collect and process experimental data, and to present and analyse results with clarity and depth
  • Know and appreciate the role and value of simulation tools when designing and analysing networks.
  • Know and gain practical experience of using network modelling tools.
COURSE CONTENT
  • UNIT 1: Layered architectures and encapsulation (OSI, TCP/IP, IEEE 802.x), standards and bodies.
  • UNIT 2: LANs, Ethernet, FDDI, IPv4, IPv6, TCP, UDP. Wide Area Networks.
  • UNIT 3: Wireless networks, Wireless PANs (ZigBee).
  • UNIT 4: Application-specific network technologies (e.g. CAN).
  • UNIT 5: Network models and their use to evaluate network performance.
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSWalter Goralski (2017). The Illustrated Network: How TCP/IP Works in a Modern Network. Massachusetts: Elsevier Inc. Richard Fox and Wei Hao (2018). Internet Infrastructure: Networking, Web Services and Cloud Computing. Boca Raton, Florida: Taylor & Francis Group
FOURTH YEAR - SEMESTER ONE
BACKGROUND AND RATIONALEInformation Retrieval module introduces learners to information retrieval. The module starts with explaining the search and analysis of unstructured data extracted from web search engines, text classification and text clustering. It proceeds to explain the various systems for collecting, indexing and searching documents. It explains the storage, organisation and access of information, as implemented in various large-scale online systems and services. The further explains the latest advancements, which underpin web search engines, text classification, text clustering and information extraction from structured and unstructured data. It explains the structure and the functionality of various systems for collecting, indexing and searching documents and ends with explaining the process of developing an advanced information retrieval system of industrial strengths.
LEARNING OUTCOMESAt the end of this module, learners should be able to:
  • Analzse and compare current approaches to requirements management within a development environment.
  • Assess the impact of stakeholders and organizational culture on the development of effective requirements and system development.
  • Relate issues associated with risk, quality, and Legal/Social/Ethical/Professional (LSEPI) to a practical scenario.
COURSE CONTENT
  • UNIT 1: Key concepts in Information Retrieval
  • UNIT 2: Boolean Retrieval, processing Boolean queries
  • UNIT 3: Dictionaries in Information Retrieval
  • UNIT 4: Index Construction
  • UNIT 5: Scoring and term weighting
  • UNIT 6: Evaluation in Information Retrieval
  • UNIT 7: XML Retrieval
  • UNIT 8: Probabilistic Retrieval
  • UNIT 9: Information Retrieval Using Machine Learning
  • UNIT 10: Vector Space and Support Vector Machines
  • UNIT 11 Flat and Hierarchical Clustering
  • UNIT 12: Web search engines, web crawling and indexing
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSCheng Xiang Zhai and Sean Massung (2016). Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining. Virginia: Association for Computing Machinery and Morgan & Claypool Publishers
BACKGROUND AND RATIONALEIT Security and Privacy Risk Management module introduces learners to IT security and privacy risk management. The module begins by giving a security and privacy overview. It explains the issues, threats and their impact on a business environment. It explains issues relating to security and privacy risks. Highlights security and privacy incidents and their management including detection and monitoring. Explains risk management. Explains the process of identifying and analysing various security and privacy risks then ends with explaining the process of security and privacy evaluation.
LEARNING OUTCOMESAt the end of this module learners should be able to:
  • Critically evaluate various security and privacy threats and their impact on an organisation,
  • Critically investigate approaches to managing and mitigating the security and privacy threats on organisations.
  • Critically evaluate the desired regulations, laws and standards that may need to be complied with to ensure the security and privacy of information systems of the organisation.
  • Apply various approaches for the evaluation of security risks, e.g., audit.
COURSE CONTENT
  • UNIT 1: Security and privacy overview.
  • UNIT 2: Issues, threats and their impact on a business environment.
  • UNIT 3: Security and privacy risks.
  • UNIT 4: Security and privacy incidents and their management including detection and monitoring.
  • UNIT 5: Risk management.
  • UNIT 6: Identification and analysis of various security and privacy risks.
  • UNIT 7: Security and privacy evaluation.
  • UNIT 8: Various frameworks (e.g., NIST, C2MS), standards (e.g., ISO27001, ISO27002), laws (e.g., Cyber Security Law) and regulations (e.g., GDPR).
  • UNIT 9: Security audit management.
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSBarry L. Williams (2013). Information Security Policy Development for Compliance: ISO/IEC 27001, NIST SP 800-53, HIPAA Standard, PCI DSS V2.0, and AUP V5.0. 2013. Boca Raton, Florida: Taylor & Francis Group. Evan Wheeler (2011). Security Risk Management: Building an Information Security Risk Management Program from the Ground Up. Massachusetts: Elsevier Inc.
BACKGROUND AND RATIONALEMachine Learning module introduces learners to machine learning. The module begins by explaining key Machine Learning principles and algorithms. It explains the theoretical background of Machine Learning and its numerous applications in science and engineering. Explains the Wide range of approaches machine learning is presented. It explains the performance and suitability of the various types of tasks and data. Explains the concept of supervised and unsupervised algorithms and their applications in real-world environments. It further explains and evaluates the optimal approaches to machine learning and ends with explaining the importance of data and their features and properties.
LEARNING OUTCOMESAt the end of this unit, you should be able to:
  • Know and critically analyse the recent advancements in Machine Learning and its ability to solve a wide range of real-world problems.
  • Conduct research on the analysis and evaluation of various advanced Machine Learning algorithms, assess and compare their functionality and performance.
  • Know and apply knowledge to design and develop a sophisticated software system, which solves a real-world domain-specific problem by utilising an appropriate machine learning approach.
COURSE CONTENT
  • UNIT 1: Main concepts in Machine Learning.
  • UNIT 2: Programming Languages and Software Tools.
  • UNIT 3: Pre-processing Data.
  • UNIT 4: Approaches to Machine Learning.
  • UNIT 5: Supervised Learning, training and testing data, active learning, classification, regression.
  • UNIT 6: Model training, overfitting and under-fitting.
  • UNIT 7: Unsupervised Learning, unsupervised networks, probabilistic methods.
  • UNIT 8: Reinforcement Learning, value function, direct policy.
  • UNIT 9: Model Evaluation and Improvement.
  • UNIT 10: Algorithm Chains and Pipelines.
  • UNIT 11: Dimensionality Reduction, principal component analysis, non-linear dimensionality reduction.
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSRudolph Russell (2018). Machine Learning: Step-by-Step Guide to Implement Machine Learning Algorithms with Python. Rudolph Russell Aurélien Géron (2017). Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems. Sebatopol: O’Reilly Media
BACKGROUND AND RATIONALEDatabase Management and Administration module introduces learners to database management and administration. The module begins by explaining the concept of database architecture; explains the process of creating the database; explains the process of managing database instance; explains the process of managing database storage structures; explains the process of managing transactional processing and locking mechanism; explains database security; explains the process of monitoring the database and using the advisors; explains the backup and recovery concepts; and ends with explaining the process of Investigating, reporting, and resolving problems.
LEARNING OUTCOMESAt the end of this unit, you should be able to:
  • Critically evaluate the concepts and tools of the database management systems.
  • Know and apply the knowledge to design, build and manage various database structures based on the specified business requirements.
  • Know and identify essential database security issues and demonstrate ability to solve them in the timely manner.
  • Develop critical awareness of issues relating to database management and practical skills to solve common database management problems
COURSE CONTENT
  • UNIT 1: Exploring the database architecture;
  • UNIT 2: Creating the database;
  • UNIT 3: Managing the database instance;
  • UNIT 4: Managing database storage structures;
  • UNIT 5: Managing transactional processing and locking mechanism;
  • UNIT 6: Database security;
  • UNIT 7: Monitoring the database and using the advisors;
  • UNIT 8: Backup and recovery concepts;
  • UNIT 9: Investigating, reporting, and resolving problems.
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSPeter Rob and Carlos Coronel (2009). Database Systems: Design, Implementation, and Management. Massachusetts: Thomson Course Technology
FOURTH YEAR - SEMESTER TWO
BACKGROUND AND RATIONALEResearch project module introduces learners to research. The module explains the process of working independently in the course of the research, explains the process of coming up with an abstract to a problem, explains how to coming up with solutions by appropriate methods, and explains how to present arguments through a user acceptance testing of the end-product/artefact as well as a well-reasoned formal dissertation report.
LEARNING OUTCOMESAt the end of this module, learners should be able to:
  • Produce a formal Project Proposal including a critical justification for the project and an appropriate set of objectives and estimates for the project.
  • Critically evaluate and use appropriate project management tools and techniques to plan, organise, schedule and control their project.
  • Undertake a critically evaluative and appropriate literature search, using a variety of sources and methods for collecting reference material.
  • Carry a software development project through to a logical conclusion.
  • Document a project with evidence of appropriate research, development methodology, technical documentation and critical refection on their progress and response to changing circumstances.
  • Satisfy any professional requirements specific to the student’s programme.
COURSE CONTENT
  • UNIT 1: Investigation, Research and Planning Methods, producing a project proposal
  • UNIT 2: Information Retrieval and Requirements Analysis, producing a literature review
  • UNIT 3: Requirements Specification Commercial and technical risk implications, LSEPi Technical Project Development
  • UNIT 4: Acceptance Testing and Evaluation
  • UNIT 5: Scoring and term weighting
  • UNIT 6: Evaluation in Information Retrieval
  • UNIT 7: XML Retrieval
  • UNIT 8: Probabilistic Retrieval
  • UNIT 9: Information Retrieval Using Machine Learning
  • UNIT 10: Vector Space and Support Vector Machines
  • UNIT 11 Flat and Hierarchical Clustering
  • UNIT 12: Web search engines, web crawling and indexing
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSBerndtsson M., Hansson J., Olsson B. and Lundell B. (2008). Thesis Projects: A Guide for Students in Computer Science and Information Systems. London: Springer-Verlag Ranjit Kumar (2011). RESEARCH METHODOLOGY: A step-by-step guide for beginners. London: SAGE Publishers
BACKGROUND AND RATIONALEEnterprise Web Software Development introduces learners to enterprise web software development. The module begins by explaining the process of agile development using scrum methodology; it explains the concept of user centred design. It explains the concept of requirements specifications and testing using user stories; explains information architecture of enterprise web sites and intranets; explains security issues; explains the process of accessibility and usability issues; explains advanced relevant programming and database concepts; explains the relevant quality assurance techniques. The module ends with highlighting the relevant legal, social, ethical and professional issues.
LEARNING OUTCOMESAt the end of this module learners should be able to:
  • Evaluate the product, team members and the development process in an agile scrum team environment with members from diverse backgrounds.
  • Synthesise and manage a wide range of technologies to meet business, security and quality requirements..
  • Know and apply the knowledge to develop creative solutions to problems, and to think independently, analytically and creatively whilst communicating clearly and effectively, in a range of forms, taking account of different audiences.
COURSE CONTENT
  • UNIT 1: Agile development using scrum methodology;
  • UNIT 2: User Centred Design;
  • UNIT 3: requirements specifications and testing using User Stories;
  • UNIT 4: Information Architecture of enterprise web sites and intranets;.
  • UNIT 5: security issues;
  • UNIT 6: accessibility and usability issues;.
  • UNIT 7: advanced relevant programming and database concepts;
  • UNIT 8: relevant Quality Assurance techniques;/li>
  • UNIT 9: relevant legal, social, ethical and professional issues.
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSChris Richardson (2019). Microservices Patterns: With Examples in Java. New York: Manning Publications Co. Kasun Indrasiri and Prabath Siriwardena (2018). Microservices for the Enterprise: Designing, Developing, and Deploying. San Jose: Kasun Indrasiri and Prabath Siriwardena
BACKGROUND AND RATIONALEApplication Development for Mobile Devices module introduces learners to applications development for mobile devices. The module begins by explaining the current trends in mobile application design and development. It highlights the unique design and development issues taken into account when developing applications for mobile devices. The module ends with explaining the native and web-based approaches and the hybrid approach where web applications are installed like native ones.
LEARNING OUTCOMESAt the end of this unit, you should be able to:
  • Demonstrate knowledge and understanding of essential facts, concepts, principles and theories relating to mobile computing and its applications.
  • Know and apply the knowledge to problem solving strategies through recognising and analysing criteria and specifications appropriate to mobile application design and implementation related problems, and plan strategies for their solution.
COURSE CONTENT
  • UNIT 1: Introduction to Mobile Computing,
  • UNIT 2: various types of mobile devices,
  • UNIT 3: Internet of Things (IoT) Native mobile application development: 3.1 two main entities – iOS and Android.
  • UNIT 4: Web-based mobile application development – 4.1 HTML5, CSS3,4.2 DOM/Javascript.
  • UNIT 5: Cross-platform hybrid development – may be PhoneGap/Cordova or a choice of platform to meet employability requirements for programming.
  • UNIT 6: Mobile Sensors – commonly available sensors in any smartphone, e.g., accelerometer, gyroscope, compass, camera and their incorporation inside a mobile application
  • UNIT 7: Mobility and Location aware applications Privacy and Security
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSMavromoustakis C.X., Mastorakis G. and Batalla J.M. (2016). Modelling and Optimization in Science and Technologies: Internet of Things (IoT). in 5G Mobile Technologies: Switzerland: Springer International Publishers B.K. Tripathy and J. Anuradha (2018). INTERNET OF THINGS (IoT): Technologies, Applications, Challenges, and Solutions. Boca Raton, Florida: Taylor and Francis Group
BACKGROUND AND RATIONALEAdvanced Networks module introduces learners to advanced networks. The module starts with explaining the process of TCP/IP reference model: Concepts and Protocols; it explains the concept of routing algorithms and protocols; it explains network performance and quality of service (QoS); explains modern network performance parameters including energy consumption in networks and ends with explaining the concept of software defined networks
LEARNING OUTCOMESAt the end of this unit, you should be able to:
  • Comprehend the principles, limitations and applications of current and future networks.
  • Critically design, analyse and evaluate different network configurations.
  • Analyse and critically evaluate the different techniques that shape the emergence of new network technologies.
  • Autonomously perform research on current networking technologies.
COURSE CONTENT
  • UNIT 1: TCP/IP Reference Model: Concepts and Protocols
  • UNIT 2: Routing Algorithms and Protocols
  • UNIT 3: Network Performance and Quality of Service (QoS)
  • UNIT 4: Modern network performance parameters including energy consumption in networks
  • UNIT 5: Software Defined Networks
ASSESMENT
Assignment 1 15%
Assignment 2 15%
Final exam 70%
Total 100%
RECOMMENDED READINGSKundu M.K, Mohapatra D.P, Konar A and Chakraborty A. (2014). Advanced Computing, Networking and Informatics Volume 2: Advanced Computing and Informatics Proceedings of the Second International Conference on Advanced Computing, Networking and Informatics. (ICACNI2014). Switzerland: Springer International Publishing Umberto Michelucci (2018). Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks. Dübendorf, Switzerland: Umberto Michelucci
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Lusaka Goldsmiths University

Sustainable transformation through innovation

Contact Us

  • 260977400886 / 260750186761
  • 260765654707
  • info@lusakagoldsmithsuniversity.ac.zm
  • Plot 52 Milima Road Woodlands PO Box 34034 Lusaka

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Lusaka Goldsmiths University

Sustainable transformation through innovation

Contact Us

  • 260977400886 / 260750186761
  • 260765654707
  • info@lusakagoldsmithsuniversity.ac.zm
  • Plot 52 Milima Road Woodlands PO Box 34034 Lusaka

Quick Links

Lusaka Goldsmiths University

Sustainable transformation through innovation

Contact Us

  • 260977400886 / 260750186761
  • 260765654707
  • info@lusakagoldsmithsuniversity.ac.zm
  • Plot 52 Milima Road Woodlands PO Box 34034 Lusaka

Quick Links

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