Baze University

Software Engineering

About the course

The Bachelor of Science (Software Engineering) programme teaches you how to apply proper engineering techniques to software development projects, building effective software products for desktops and mobile devices.
Information communication technology (ICT) continues to play a crucial part in effective computer systems that can meet increasing user demands.


We live in a world dominated by online services and social interactions, so the ICT systems behind them must be responsive, reliable and secure. This practical course covers the development and use of ICT systems in business and industry, and focuses on core business technologies.

While we concentrate on developing the skills you need to understand an organisation's information and technical needs, you'll also study elements of computer programming and gain additional skills for a career in technical and end-user support, or application development.

The programme philosophy is that computing and information systems concepts and practices have to be complemented by organisational and management concepts and practices in order to be effective. The programme provides students with theoretical knowledge and practical skills in both areas, enabling graduates to contribute to the effective development and exploitation of information systems and technology in companies, organisations and society as a whole.

It is recognised that today's skills are often transitory, especially in computing and information systems. Therefore the programme strikes a balance between learning current skills and emphasizing the underlying theories which justify the choice of one skill set rather than another. The fundamental theories last longer than particular skills and provide a sound basis for understanding and evaluating new developments in computer science and information systems.

Our Software Engineering programme provides a strong technical basis, together with a functional management focus, ensuring graduates have the right combination of business awareness and technical ability.

The programme is designed to enable you, as a software engineer, business analyst or consultant, to leverage the use of computing systems within organisations.

What you will learn

The course aims:
with a strong focus on programming, this course includes software development, database and networking units.
covered technologies include Java, Android, Oracle SQL, PHP, Web API's, JSON, HTML5, jQuery and big data analytics;
students work on a range of projects, producing a portfolio of completed work which they can refer back to throughout their career.;
students learning is supported by the use of industry standard facilities. These include high-spec IT suites and a professional usability lab;
this programme includes optional units in the second and third year, enabling students to develop specialisms and improve their career prospects;
to provide the foundation for a professional career in the computing-based industries, including telecommunications, process control, business-, mission-, and safety-critical fields;
to enhance the skills of a professional who is already working in one of these industries;
to present knowledge, experience, reasoning methods and design and implementation techniques that are robust and forward-looking.

Graduate destinations

Programmer
Software Engineer
Program Analyst
System Analyst

Course Details

Course Structure
Year 3 | Semester 1
Code: COM211
Lecturer: Mrs Lawrence Morolake Oladayo
Unit: 0
Prerequisite: No Prerequisite
Overview:
Aims:
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Code: COM321
Lecturer: Julius Makinde
Unit: 3
Prerequisite: No Prerequisite
Overview:

Data Communication and Networking has change the way we interact and share information. The positive impact of this module on the way we do business cannot be over emphasized. Information sharing can be local or remote (distance). In this module, students will learn more about distance communication. They will explore some basic theories of hardware (electronics devices) and software components of communication. 

Aims:

  • Expose the students to the role of each component of communication and their interconnection. 
  • Explore the different Network layout. 
  • Understand various forms of data that can be transmitted over a network.
Syllabus:

Introduction to Networking, Components of Communication, Open System Interconnection (OSI) Reference Model, Network Topology, Introduction to Network Addresses, Network Devices, Network standards. Transmission medium, Concept of packet and Circuit switching.

Teaching and learning methods:

  • Lectures will be used to explain the content of the syllabus.
  • Class discussion will be used to stimulate students’ participation and sharing of knowledge to develop their communication skill. 
  • There will be hands on experience in the laboratory to enhance the understanding of most of the topics taught in the classroom.
Intended learning outcomes:

  • On completion of this module, student should be able to:
  • Define the basic terminologies of Computer Networks
  • Terminate twisted pair cable
  • Use various communication devices to setup a network
  • Understand communication delays and how to eliminate it
  • Understand the best network solution for any given environment
Assessment:
Exams: 60%
Test: 15%
Quiz: 10%
Coursework: 15%
Recommended reading list:

Data Communications and Networking 5th Editon - 2012 (Behrouz A.)

Cabling: The Complete Guide to Network Wiring (David Barnett, David Groth and Jim McBee)

Computer Networking: A Top-Down Approach: Kurose (6th or 7th Edition)


Code: COM304
Lecturer: Sabiu Maikore Fatima
Unit: 3
Prerequisite: No Prerequisite
Overview:

This module will enable students to develop a critical and practical understanding of concepts in databases with a primary focus on data modelling and implementation. 

Aims:

Teaching, learning and assessment of the module will support these aims:

Basic knowledge of concepts in information systems 

An understanding of the concepts in database systems including the evolution from file system to database systems

Data modelling concepts, techniques and methods

An understanding of different types of data models

Skills in structured query language, and query optimization

An understanding of database administration and security issues as well as ethical concerns in data management


Syllabus:

Introduction to Information Systems, Introduction to Databases, Data Models, Relational Database Model, Data Modeling with ER diagrams, Extended ER modeling, Normalization, Structured Query Language (SQL), SQL queries, constraints and triggers,  Query optimization, Database administration, Database security, Interacting with databases through the web, NoSQL databases, Ethical issues in data management.


Teaching and learning methods:

There will be approximately 3 hours of lectures and 2 hours of workshop sessions every week. Lectures will be delivered in an engaging manner and students are expected to participate in discussions. The workshops will be designed to allow students practice the concepts taught during the lectures using appropriate tools such as MySQL Workbench, ERwin Data Modeller and MS SQL Server.

Intended learning outcomes:

In order to get a pass grade in this module, students must meet these learning outcomes:

Demonstrate knowledge of concepts in database systems

Be able to use data modelling tools and RDBMS

Demonstrate skills in structured query language

Reflect critically on how to handle database administration and security challenges


Assessment:
Exams: 60%
Test: 5%
Quiz: 5%
Coursework: 30%
Recommended reading list:

Coronel, C., Morris, S., & Rob, P. Database Principles: Fundamentals of Design, Implementation, and Management.

Code: BUS305
Lecturer: Bilkisu Abubakar
Unit: 0
Prerequisite: No Prerequisite
Overview:
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Code: COM301
Lecturer: Charles Isah Saidu
Unit: 3
Prerequisite: Algorithms ,
Overview:

The concepts of algorithm, role of abstraction in algorithm design, design and analysis of algorithms, divide and conquer algorithms including sorting and convex hull, greedy algorithms including job sequencing, shortest path and spanning trees, dynamic programming including knapsack and travelling salesman problem.

Aims:

The aim of this module is to explain the concepts of algorithms, algorithm design & analysis of algorithms and also to identify, describe and have an in depth knowledge of different algorithm types with their examples.

Syllabus:

Fundamentals of Algorithmic Problem Solving.

Fundamentals of the Analysis of Algorithm Efficiency.

Divide and Conquer Algorithm. Greedy Algorithm.

Dynamic Programming.

Teaching and learning methods:
  • Lectures will be used to introduce and explain major ideas, theories and to illustrate their wide- ranging applications
  • Interactive lectures will review materials by encouraging the student active participation - inviting questions, working through examples, giving short quizzes, discussing case studies etc.
  • Classes will encourage the student to apply the knowledge gained to real and hypothetical cases and will encourage students to gain confidence in presenting and defending their own ideas. Classes will usually require the student to read some material for discussion, or prepare answers, give some presentations, research a topic etc.
  • Class-work and Homework will be assigned regularly. These will help the students to understand the material .The answers to the homework should be clear, concise and correct.
  • Intended learning outcomes:

    On the successful completion of this module the student should understand and be able to:-

    • Understand the concepts of different Algorithms.
    • Understand the different algorithms and their features.
    • Design and Analyse algorithms efficiently.
    • Have a good knowledge on how to implement pseudo codes of these algorithms using a programming language.
    • Understand the different applications of these algorithms.

    Assessment:
    Exams: 60%
    Test: 20%
    Quiz: 10%
    Coursework: 10%
    Recommended reading list:
    1. Levitin, A. (2011).Introduction to Design and Analysis of Algorithms.3 rd ed. Pearson.
    2. Sedgewick,R. & Flajolet,P. (2013).An Introduction to the Analysis of algorithms.2nd ed.Addison-Wesley.
    3. Soltys,M. (2012).An Introduction to the analysis of algorithms.2 nd ed.World Scientific. Singapore.
    4. Skiena,S.(1997).The Algorithm designmanual.Springer-Verlag.Newyork.
    Code: MTH201
    Lecturer: Benjamin Oyelami Oyediran
    Unit: 0
    Prerequisite: No Prerequisite
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    Code: COM205
    Lecturer: Nasiru Aboki
    Unit: 5
    Prerequisite: No Prerequisite
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    Code: COM307
    Lecturer: Samuel Ubaru
    Unit: 10
    Prerequisite: No Prerequisite
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    Year 3 | Semester 2
    Code: GEN301
    Lecturer: Ojeme Tope
    Unit: 0
    Prerequisite: No Prerequisite
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    Code: COM313
    Lecturer: Essien Udoh Kevac
    Unit: 15
    Prerequisite: No Prerequisite
    Overview:
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    Code: COM399
    Lecturer: Mubaraka Sani Ibrahim
    Unit: 0
    Prerequisite: No Prerequisite
    Overview:
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    Code: COM306
    Lecturer: Sylvanus A. Ehikioya
    Unit: 3
    Prerequisite: Computer Systems 2 ,
    Overview:

    Introduction to operating systems, core concepts of operating systems, types of operating systems, kernels, processes and threads, concurrency and synchronization, deadlocks and prevention, resource management – memory, storage units, file systems and CPU time.

    Aims:

    The aim of this module is to expose the students to the concepts of operating systems, its design and implementation techniques. It identifies and describes the major and common components of an operating system, and introduce to students the concepts of a process, threads, resource management (memory, storage units, file systems and CPU time).

    Syllabus:

    Operating Systems Structures. Process Management. 

    Memory Management. Storage Management. Protection and Security. Case studies of Windows and Linux Operating Systems.

    Teaching and learning methods:

    • Lectures will be used to introduce and explain major ideas, theories and to illustrate their wide- ranging applications.

    • Interactive lectures will review materials by encouraging the student active participation - inviting questions, working through examples, giving short quizzes, discussing case studies etc.
    • Classes will encourage the student to apply the knowledge gained to real and hypothetical cases and will encourage students to gain confidence in presenting and defending their own ideas. Classes will usually require the student to read some material for discussion, or prepare answers, give some presentations, research a topic etc.
    • Class-work and Homework will be assigned regularly. These will help the students to understand the material .The answers to the homework should be clear, concise and correct.

    Intended learning outcomes:

    On the successful completion of this module the student should understand and be able to:-


    • The students will have a working knowledge of operating systems’ theory and practice.
    • The students will have a knowledge of the factors that influence the design and type of operating systems.
    • The students will understand the concept of a kernel, process, process management, thread and the relationship between a process and a thread.
    •  The students will understand some Resource management techniques for memory, storage units etc

    Assessment:
    Exams: 60%
    Test: 20%
    Quiz: 10%
    Coursework: 10%
    Recommended reading list:

    1. Operating System Concepts, Silberschatz A., Galvin P.B.,(2013) John Wiley & Sons Inc., ISBN 978 118 06333 0, Ninth Edition

    2. Operating System Concepts with Java, Silberschatz A., Galvin P.B.,(2010) John Wiley& Sons Inc.,ISBN 978 0 470 50849 4 .Eight Edition

    3. Modern Operating Systems" by Tanenbaum, A.S., Prentice Hall, 3rd edition, 2009.

    4. Modern Operating Systems, Garridon J., Schlesinger R. & Hoganson K. Jones & Bartlett learning LLC. 2nd edition, 2013.

    5. Operating Systems: Internal and Design Principles" by Stallings, W., Prentice Hall, 7th edition, 2012

    Code: COM402
    Lecturer: Peter Ogedebe
    Unit: 3
    Prerequisite: No Prerequisite
    Overview:

    The Research Methods module introduces the students to the concept of research in computing, the different chapters present in the documentation and how to go about acquiring data and necessary information. This module does not only concentrate on the theoretical teachings of research but is also used to prepare the students for their final year documentation.

    Aims:
    To provide the students with an explicit understanding of their final project documentation deliverables. The project has five main chapters and each student should be able to aptly write content for each of these chapters in a concise and standard manner.
    To aid students apply the knowledge they have garnered in their previous years. This knowledge will then be practically transformed into their project (regardless of their discipline/majors).
    To apply the concept of research methods during the formation of the introduction, literature review, requirements, and design chapters of their documentation.

    Syllabus:

    Introduction to Research: Lecture on the definition, characteristics, and evaluation of academic research. Emphasis on the generation, development and refining of ideas into full-fledged project proposals. Research Methods Definition: Lecture on the definition of research methods and the types. Research Ethics: Lecture on the importance of ethics in research and the consequences of Plagiarism.

    Teaching and learning methods:

    Interactive Lecture – Ideas from both students and lecturer will be introduced and discussed in a discussion-oriented scenario. 

    Lecture – New concepts on research, the different forms of research, research motivations and the guidelines to follow when conducting research will be introduced.

    Thesis Compilation – Because the course is meant to help prepare the documentation for the final year project, students will not have assignments but will rather provide versions of the first three chapters of their documentation. Each completed chapter will be used as part of their continuous assessment to motivate them.


    Intended learning outcomes:

    • Students will have a profound understanding of the methods and approaches they will follow while conducting research projects.
    • Students will have completed the first three chapters of their final year project documentation

    Assessment:
    Exams: 70%
    Test: 10%
    Quiz: 5%
    Coursework: 15%
    Recommended reading list:


    Code: GEN300
    Lecturer: Omonayin Esther T.
    Unit: 0
    Prerequisite: No Prerequisite
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    Code: COM302
    Lecturer: Amit Mishra
    Unit: 0
    Prerequisite: No Prerequisite
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    Year 4 | Semester -
    Code: COM411
    Lecturer: Khadijah Mohammed Danjuma
    Unit: 0
    Prerequisite: No Prerequisite
    Overview:
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    Code: LAW519
    Lecturer: Dayo Godwin Ashonibare
    Unit: 0
    Prerequisite: No Prerequisite
    Overview:
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    Code: COM421
    Lecturer: Chandrasekhar Uppin
    Unit: 3
    Prerequisite: Programming 1 , Programming 2 , Web Programming , Application Programming with Java/C# ,
    Overview:

    The purpose of this module is to provide students with a coherent knowledge of internal (low-level) structure of existing Programming Languages, how instructions are identified, translated and compiled/interprets during the execution. Understanding Semantics, lexical, and Syntactical structure of programming languages with its analysis.   Identifying the style of Programming, cconcept of computational  paradigm, understand the design criteria, to know more about Logic & Logic Programs and to understanding Lexics Vs Syntax Vs Semantics,  data types and control structures.

    Aims:

    Aim to introduce this module to know more about the internal structure of Programming Languages.  How Programming Languages are designed and created for various applications. 

    Course designed to intend :  

    • To understand the concept of computational  paradigm
    • To understand the design criteria
    • To understand functional programming
    • To know more about Logic & Logic Programs 
    • Lexical and Syntax analysis  
    • Abstract data type and Modules.
    • To understanding Lexical Vs Syntax Vs Semantics,  data types and control structures.


    Syllabus:

    Introduction to programming languages, compilers and interpreters, abstract machines, programming language grammar and syntax, compilers, the compilation process, parsing, semantics, pragmatics, implementation, expressiveness of programming languages, data structures, memory management, control structures, structured programming, recursion, subprograms, high-order functions, exceptions, data abstraction, object-oriented, functional and logic programming paradigms, historical perspective.

    Teaching and learning methods:

    • During the Lectures discussing the concepts of Imperative and Object Oriented Programming Language practices with its structure. 
    • Interactive lectures will review course materials by encouraging the student active participation - inviting questions / discussions, working through examples given in case studies.
    • In Leaning process students will be encourage to use and applied their existing knowledge to enhance the confidence level within. Organized case study presentation to encourage students to motive self-preparation and transformation of knowledge with various research approaches. 
    • To easy understanding the subject providing ample Hands on work (Assignments Direct/Applied) Case study practices which are helps the student to understand the more applied. As this course in 400 level. 

    Intended learning outcomes:

    On the successful completion of this module the student should understand :-

    • Understand the Low-level structure of programming languages.
    • Understand how Language instructions are identified, translated and compiled/interprets during the execution.
    • Understand the available style of programming languages in the market and current use.
    • Understanding Lexical Vs Syntax Vs Semantics,  data types and control structures of  its usage in programming languages with their  effects & efficiency.
    • Capable of choosing appropriate programming languages to design and build different kinds of applications.


    Assessment:
    Exams: 70%
    Test: 10%
    Quiz: 5%
    Coursework: 15%
    Recommended reading list:

    Kenneth C. Louden, Programming Languages: Principles and Practice, 3rd edition PWS Publishing (Boston), 1993.

    Other Sources:

    Paul Hudak, “Conception, Evolution, and Application of Functional Programming Languages,” ACM Computing Surveys 21/3, 1989, pp 359-411.

    Clocksin and Mellish, Programming in Prolog, Springer Verlag, 1987


    Code: COM401
    Lecturer: Mohammed Hammawa Baba
    Unit: 0
    Prerequisite: No Prerequisite
    Overview:
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    Code: COM309
    Lecturer: Sabiu Maikore Fatima
    Unit: 3
    Prerequisite: No Prerequisite
    Overview:

    This module will enable students to develop a critical and practical understanding of concepts, standards and frameworks for the semantic web with a primary focus on the semantic web technologies.

    Aims:

    Teaching, learning and assessment of the module will support these aims:

    Reflection on conceptual foundations of the Semantic Web

    Introduction to XML basics to ease students into further Semantic Web languages.

    Experience and exposure to Semantic Web languages, such as RDF(S) and OWL. The course, however, does not attempt to cover the languages comprehensively.

    Practical experience on data modelling through the development of simple ontologies using Protégé tool.

    An understanding of SPARQL. 

    Practical experience on querying semantic repositories using SPARQL.


    Syllabus:

    Introduction to the semantic web, The semantic web vision, XML basics, Resource description framework (RDF), RDF schema language, SPARQL infrastructure, Matching patterns, Construct queries , SPARQL update, Basics of Web Ontology Language (OWL),  OWL , Applications on the semantic web, Ontology engineering, Semantic web application architechture, Logic and inference: rules.


    Teaching and learning methods:

    There will be approximately 3 hours of lectures and 2 hours of workshop sessions every week. Lectures will be delivered in an engaging manner and students are expected to participate in discussions. The workshops will be designed to allow students practice the concepts taught during the lectures.

    Intended learning outcomes:

    In order to get a pass grade in this module, students must meet these learning outcomes:

    Reflect critically on how adding semantics can transform the traditional Web. 

    Demonstrate an awareness of the core concepts that provide a foundation for the Semantic Web.

    Be able to use appropriate tools to create simple ontologies to represent concepts in any domain.

    Demonstrate the ability to use appropriate tools to create and execute SPARQL queries. 


    Assessment:
    Exams: 60%
    Test: 10%
    Quiz: 5%
    Coursework: 25%
    Recommended reading list:

    Antoniou, G., Groth, P., van Harmelen, F., Hoekstra, R., A Semantic Web Primer.

    Year 4 | Semester -
    Code: COM212
    Lecturer: Moses Obioma Ubaru
    Unit: 0
    Prerequisite: No Prerequisite
    Overview:
    Aims:
    Syllabus:
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    Code: COM413
    Lecturer: Mohammed Hammawa Baba
    Unit: 3
    Prerequisite: No Prerequisite
    Overview:

    At the end of this Module, it is expected that participants will appreciate the major role played by Information and Communication Technology (ICT) tools in investigating and producing acceptable forensic evidence in an organizational context and criminal breach of Laws. This module identifies the various offences committed using ICT tools and how they can be investigated given the various restrictions available in their contexts, noting that a breach of organizational policy might not necessarily culminate in a breach of law. This module addresses the question “that in the event a breach of law occurs or both, what technical, policy-driven, and legal procedures (such as E-voting and audits, etc.) should be taken to provide evidence and how?”

    Aims:
    • To aid students to have sound understanding of the theories and concepts of Forensic Investigations as it applies to computers, networks, and application software and general electronic devices.
    • To aid students to understand and apply Current Basic Information Technologies in its diverse variations to network design, software development, Data or information management investigating incidences, criminal acts conducted using Information technology
    • To provide an appreciation of the application of breach of Security policies and standards to real and hypothetical cases in technical and legal terms, given legal and organizational constraints, while understanding the trade-offs involved in the application of security policies.

    Syllabus:

    Understanding Computer Investigations, Current Computer Forensics Tools, Processing Crime and Incident Scenes, Data Acquisition, Working with Windows and DOS Systems, Macintosh and Linux Boot Processes and File Systems, Computer Forensics Analysis and Validation, Recovering Graphics Files, Virtual Machines, Network Forensics, and Live Acquisitions, Cell Phone and Mobile Devices Forensics, E-mail Investigations, Legal issues and Report Writing for High-Tech Investigations

    Teaching and learning methods:
    • Lectures: Lectures will be used to introduce and explain major ideas, theories and to illustrate their wide-ranging applications. You will be handed the lecture folder and background reading materials. You are expected to have read these materials before the next class so we can discuss these in line with the weeks lecture.
    • Interactive lectures will review materials by encouraging your active participation - inviting questions, working through examples, giving short quizzes, discussing case studies, or showing a  video followed by a quiz, etc. Thus, this session forgoes the standard Socratic Method for a more conversational framework.
    • Classes: Classes will encourage you to begin to apply the knowledge gained to real and hypothetical cases and will encourage students to gain confidence in presenting and defending their own ideas. Classes will usually require you to read some material for discussion, or prepare answers, give some presentations, research a topic, take part in a debate, etc. 

    Intended learning outcomes:
    On Completion of the module the student should be able to:

    • Demonstrate an understanding of Basic Computer Forensic Concepts and best practices;
    • Be able to apply these concepts to real world scenarios and cases using ethical principles required of computer professionals;
    • Be able to identify and recommend appropriate tools for various Forensic Investigations while analyzing  case-requirements using best practices and current methodologies;
    • Be able to apply technical skill set in carrying out forensic investigations on digital devices
    • Show sound understanding of existing laws and guidelines for admissibility of evidence discovered
      the concept of an expert witness and its requirement
    Assessment:
    Exams: 60%
    Test: 15%
    Quiz: 10%
    Coursework: 15%
    Recommended reading list:

    • Incidence Response and Computer Forensics; Second and Third Edition, Kevin Mandia, Mathew pepe et al, (Primary text)
    • Real Digital Forensics: Computer Security and Incident Response, Keith Jones, Curtis Rose et al. (Secondary Text)
    • And recommended Journals  on special topics

    Code: COM403
    Lecturer:
    Unit: 0
    Prerequisite: No Prerequisite
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    Entry requirements

    Home / UTME


    SSCE (WAEC, NECO, etc);
    JAMB;

    Home / Direct Entry


    A level / Diploma / IJMB / HND / First degree;
    JAMB DE Form;
    SSCE (WAEC, NECO, etc);

    Home / Direct Transfer


    SSCE (WAEC, NECO, etc);
    Academic transcript;
    Please note: Admission on transfer will only be issued after on campus interview;

    Foundation


    SSCE (WAEC, NECO, etc);

    International (Nigerian)


    O' level result;
    JAMB;
    Please note: You can get a conditional admission if you does not have JAMB, but you must provide it before you progress to 200 level;

    International (Foreign)


    O' level result;

    Staff

    There are no staff for this course